---
_id: '60990'
abstract:
- lang: eng
text: 'Large Language Models (LLMs) have demonstrated remarkable performance across
a wide range of natural language processing tasks. However, their effectiveness
in low-resource languages remains underexplored, particularly in complex tasks
such as end-to-end Entity Linking (EL), which requires both mention detection
and disambiguation against a knowledge base (KB). In earlier work, we introduced
IndEL — the first end-to-end EL benchmark dataset for the Indonesian language
— covering both a general domain (news) and a specific domain (religious text
from the Indonesian translation of the Quran), and evaluated four traditional
end-to-end EL systems on this dataset. In this study, we propose ELEVATE-ID, a
comprehensive evaluation framework for assessing LLM performance on end-to-end
EL in Indonesian. The framework evaluates LLMs under both zero-shot and fine-tuned
conditions, using multilingual and Indonesian monolingual models, with Wikidata
as the target KB. Our experiments include performance benchmarking, generalization
analysis across domains, and systematic error analysis. Results show that GPT-4
and GPT-3.5 achieve the highest accuracy in zero-shot and fine-tuned settings,
respectively. However, even fine-tuned GPT-3.5 underperforms compared to DBpedia
Spotlight — the weakest of the traditional model baselines — in the general domain.
Interestingly, GPT-3.5 outperforms Babelfy in the specific domain. Generalization
analysis indicates that fine-tuned GPT-3.5 adapts more effectively to cross-domain
and mixed-domain scenarios. Error analysis uncovers persistent challenges that
hinder LLM performance: difficulties with non-complete mentions, acronym disambiguation,
and full-name recognition in formal contexts. These issues point to limitations
in mention boundary detection and contextual grounding. Indonesian-pretrained
LLMs, Komodo and Merak, reveal core weaknesses: template leakage and entity hallucination,
respectively—underscoring architectural and training limitations in low-resource
end-to-end EL.11Code and dataset are available at https://github.com/dice-group/ELEVATE-ID.'
article_type: original
author:
- first_name: Ria Hari
full_name: Gusmita, Ria Hari
id: '71039'
last_name: Gusmita
- first_name: Asep Fajar
full_name: Firmansyah, Asep Fajar
id: '76787'
last_name: Firmansyah
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Gusmita RH, Firmansyah AF, Zahera HMA, Ngonga Ngomo A-C. ELEVATE-ID: Extending
Large Language Models for End-to-End Entity Linking Evaluation in Indonesian.
Data & Knowledge Engineering. 2026;161:102504. doi:https://doi.org/10.1016/j.datak.2025.102504'
apa: 'Gusmita, R. H., Firmansyah, A. F., Zahera, H. M. A., & Ngonga Ngomo, A.-C.
(2026). ELEVATE-ID: Extending Large Language Models for End-to-End Entity Linking
Evaluation in Indonesian. Data & Knowledge Engineering, 161,
102504. https://doi.org/10.1016/j.datak.2025.102504'
bibtex: '@article{Gusmita_Firmansyah_Zahera_Ngonga Ngomo_2026, title={ELEVATE-ID:
Extending Large Language Models for End-to-End Entity Linking Evaluation in Indonesian},
volume={161}, DOI={https://doi.org/10.1016/j.datak.2025.102504},
journal={Data & Knowledge Engineering}, author={Gusmita, Ria Hari and Firmansyah,
Asep Fajar and Zahera, Hamada Mohamed Abdelsamee and Ngonga Ngomo, Axel-Cyrille},
year={2026}, pages={102504} }'
chicago: 'Gusmita, Ria Hari, Asep Fajar Firmansyah, Hamada Mohamed Abdelsamee Zahera,
and Axel-Cyrille Ngonga Ngomo. “ELEVATE-ID: Extending Large Language Models for
End-to-End Entity Linking Evaluation in Indonesian.” Data & Knowledge Engineering
161 (2026): 102504. https://doi.org/10.1016/j.datak.2025.102504.'
ieee: 'R. H. Gusmita, A. F. Firmansyah, H. M. A. Zahera, and A.-C. Ngonga Ngomo,
“ELEVATE-ID: Extending Large Language Models for End-to-End Entity Linking Evaluation
in Indonesian,” Data & Knowledge Engineering, vol. 161, p. 102504,
2026, doi: https://doi.org/10.1016/j.datak.2025.102504.'
mla: 'Gusmita, Ria Hari, et al. “ELEVATE-ID: Extending Large Language Models for
End-to-End Entity Linking Evaluation in Indonesian.” Data & Knowledge Engineering,
vol. 161, 2026, p. 102504, doi:https://doi.org/10.1016/j.datak.2025.102504.'
short: R.H. Gusmita, A.F. Firmansyah, H.M.A. Zahera, A.-C. Ngonga Ngomo, Data &
Knowledge Engineering 161 (2026) 102504.
date_created: 2025-08-24T11:38:51Z
date_updated: 2025-08-25T09:40:13Z
department:
- _id: '574'
doi: https://doi.org/10.1016/j.datak.2025.102504
intvolume: ' 161'
keyword:
- LLMs
- Evaluation
- End-to-end EL
- Indonesian
language:
- iso: eng
main_file_link:
- url: https://www.sciencedirect.com/science/article/pii/S0169023X25000990?utm_campaign=STMJ_220042_AUTH_SERV_PA&utm_medium=email&utm_acid=78351008&SIS_ID=&dgcid=STMJ_220042_AUTH_SERV_PA&CMX_ID=&utm_in=DM591673&utm_source=AC_
page: '102504'
publication: Data & Knowledge Engineering
publication_identifier:
issn:
- 0169-023X
status: public
title: 'ELEVATE-ID: Extending Large Language Models for End-to-End Entity Linking
Evaluation in Indonesian'
type: journal_article
user_id: '71039'
volume: 161
year: '2026'
...
---
_id: '62723'
abstract:
- lang: eng
text: Structural measures of graphs, such as treewidth, are central tools in computational
complexity resulting in efficient algorithms when exploiting the parameter. It
is even known that modern SAT solvers work efficiently on instances of small treewidth.
Since these solvers are widely applied, research interests in compact encodings
into (Q)SAT for solving and to understand encoding limitations. Even more general
is the graph parameter clique-width, which unlike treewidth can be small for dense
graphs. Although algorithms are available for clique-width, little is known about
encodings. We initiate the quest to understand encoding capabilities with clique-width
by considering abstract argumentation, which is a robust framework for reasoning
with conflicting arguments. It is based on directed graphs and asks for computationally
challenging properties, making it a natural candidate to study computational properties.
We design novel reductions from argumentation problems to (Q)SAT. Our reductions
linearly preserve the clique-width, resulting in directed decomposition-guided
(DDG) reductions. We establish novel results for all argumentation semantics,
including counting. Notably, the overhead caused by our DDG reductions cannot
be significantly improved under reasonable assumptions.
author:
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Markus
full_name: Hecher, Markus
last_name: Hecher
- first_name: Johanna
full_name: Groven, Johanna
last_name: Groven
- first_name: Johannes K.
full_name: Fichte, Johannes K.
last_name: Fichte
citation:
ama: Mahmood Y, Hecher M, Groven J, Fichte JK. Structure-Aware Encodings of Argumentation
Properties for Clique-width. Pre-print of paper accepted at AAAI 2026.
Published online 2026.
apa: Mahmood, Y., Hecher, M., Groven, J., & Fichte, J. K. (2026). Structure-Aware
Encodings of Argumentation Properties for Clique-width. In Pre-print of paper
accepted at AAAI 2026.
bibtex: '@article{Mahmood_Hecher_Groven_Fichte_2026, title={Structure-Aware Encodings
of Argumentation Properties for Clique-width}, journal={Pre-print of paper accepted
at AAAI 2026}, author={Mahmood, Yasir and Hecher, Markus and Groven, Johanna and
Fichte, Johannes K.}, year={2026} }'
chicago: Mahmood, Yasir, Markus Hecher, Johanna Groven, and Johannes K. Fichte.
“Structure-Aware Encodings of Argumentation Properties for Clique-Width.” Pre-Print
of Paper Accepted at AAAI 2026, 2026.
ieee: Y. Mahmood, M. Hecher, J. Groven, and J. K. Fichte, “Structure-Aware Encodings
of Argumentation Properties for Clique-width,” Pre-print of paper accepted
at AAAI 2026. 2026.
mla: Mahmood, Yasir, et al. “Structure-Aware Encodings of Argumentation Properties
for Clique-Width.” Pre-Print of Paper Accepted at AAAI 2026, 2026.
short: Y. Mahmood, M. Hecher, J. Groven, J.K. Fichte, Pre-Print of Paper Accepted
at AAAI 2026 (2026).
date_created: 2025-12-01T12:05:05Z
date_updated: 2025-12-04T21:09:06Z
department:
- _id: '574'
external_id:
arxiv:
- '2511.10767'
language:
- iso: eng
publication: Pre-print of paper accepted at AAAI 2026
status: public
title: Structure-Aware Encodings of Argumentation Properties for Clique-width
type: preprint
user_id: '99353'
year: '2026'
...
---
_id: '62721'
abstract:
- lang: eng
text: We introduce the notion of contrastive ABox explanations to answer questions
of the type "Why is a an instance of C, but b is not?". While there are various
approaches for explaining positive entailments (why is C(a) entailed by the knowledge
base) as well as missing entailments (why is C(b) not entailed) in isolation,
contrastive explanations consider both at the same time, which allows them to
focus on the relevant commonalities and differences between a and b. We develop
an appropriate notion of contrastive explanations for the special case of ABox
reasoning with description logic ontologies, and analyze the computational complexity
for different variants under different optimality criteria, considering lightweight
as well as more expressive description logics. We implemented a first method for
computing one variant of contrastive explanations, and evaluated it on generated
problems for realistic knowledge bases.
author:
- first_name: Patrick
full_name: Koopmann, Patrick
last_name: Koopmann
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Balram
full_name: Tiwari, Balram
last_name: Tiwari
citation:
ama: Koopmann P, Mahmood Y, Ngonga Ngomo A-C, Tiwari B. Can You Tell the Difference?
Contrastive Explanations for ABox Entailments. Pre-print of paper accepted
at AAAI 2026. Published online 2026.
apa: Koopmann, P., Mahmood, Y., Ngonga Ngomo, A.-C., & Tiwari, B. (2026). Can
You Tell the Difference? Contrastive Explanations for ABox Entailments. In Pre-print
of paper accepted at AAAI 2026.
bibtex: '@article{Koopmann_Mahmood_Ngonga Ngomo_Tiwari_2026, title={Can You Tell
the Difference? Contrastive Explanations for ABox Entailments}, journal={Pre-print
of paper accepted at AAAI 2026}, author={Koopmann, Patrick and Mahmood, Yasir
and Ngonga Ngomo, Axel-Cyrille and Tiwari, Balram}, year={2026} }'
chicago: Koopmann, Patrick, Yasir Mahmood, Axel-Cyrille Ngonga Ngomo, and Balram
Tiwari. “Can You Tell the Difference? Contrastive Explanations for ABox Entailments.”
Pre-Print of Paper Accepted at AAAI 2026, 2026.
ieee: P. Koopmann, Y. Mahmood, A.-C. Ngonga Ngomo, and B. Tiwari, “Can You Tell
the Difference? Contrastive Explanations for ABox Entailments,” Pre-print of
paper accepted at AAAI 2026. 2026.
mla: Koopmann, Patrick, et al. “Can You Tell the Difference? Contrastive Explanations
for ABox Entailments.” Pre-Print of Paper Accepted at AAAI 2026, 2026.
short: P. Koopmann, Y. Mahmood, A.-C. Ngonga Ngomo, B. Tiwari, Pre-Print of Paper
Accepted at AAAI 2026 (2026).
date_created: 2025-12-01T12:03:06Z
date_updated: 2025-12-04T21:08:32Z
department:
- _id: '574'
external_id:
arxiv:
- '2511.11281'
language:
- iso: eng
publication: Pre-print of paper accepted at AAAI 2026
status: public
title: Can You Tell the Difference? Contrastive Explanations for ABox Entailments
type: preprint
user_id: '99353'
year: '2026'
...
---
_id: '54450'
abstract:
- lang: eng
text: In the last decade, there has been increasing interest in allowing users to
understand how the predictions of machine-learned models come about, thus increasing
transparency and empowering users to understand and potentially contest those
decisions.Dialogue-based approaches, in contrast to traditional one-shot eXplainable
Artificial Intelligence (XAI) methods, facilitate interactive, in-depth exploration
through multi-turn dialogues, simulating expert conversations. This paper reviews
the current state of dialogue-based XAI, presenting a systematic review of 1,339
publications, narrowed down to 14 based on inclusion criteria. We explore theoretical
foundations of the systems, propose key dimensions along which different solutions
to dialogue-based XAI differ, and identify key use cases, target audiences, system
components, and the types of supported queries and responses. Furthermore, we
investigate the current paradigms by which systems are evaluated and highlight
their key limitations. Key findings include identifying the main use cases, objectives,
and audiences targeted by dialogue-based XAI methods, and summarize the main types
of questions and information needs. Beyond discussing avenues for future work,
we present a meta-architecture for these systems from existing literature and
outlined prevalent theoretical frameworks.
article_number: '81'
author:
- first_name: Dimitry
full_name: Mindlin, Dimitry
last_name: Mindlin
- first_name: Fabian
full_name: Beer, Fabian
last_name: Beer
- first_name: Leonie Nora
full_name: Sieger, Leonie Nora
id: '93402'
last_name: Sieger
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Philipp
full_name: Cimiano, Philipp
last_name: Cimiano
- first_name: Elena
full_name: Esposito, Elena
last_name: Esposito
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Mindlin D, Beer F, Sieger LN, et al. Beyond One-Shot Explanations: A Systematic
Literature Review of Dialogue-Based XAI Approaches. Artificial Intelligence
Review. 2025;58(3). doi:10.1007/s10462-024-11007-7'
apa: 'Mindlin, D., Beer, F., Sieger, L. N., Heindorf, S., Cimiano, P., Esposito,
E., & Ngonga Ngomo, A.-C. (2025). Beyond One-Shot Explanations: A Systematic
Literature Review of Dialogue-Based XAI Approaches. Artificial Intelligence
Review, 58(3), Article 81. https://doi.org/10.1007/s10462-024-11007-7'
bibtex: '@article{Mindlin_Beer_Sieger_Heindorf_Cimiano_Esposito_Ngonga Ngomo_2025,
title={Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based
XAI Approaches}, volume={58}, DOI={10.1007/s10462-024-11007-7},
number={381}, journal={Artificial Intelligence Review}, publisher={Springer},
author={Mindlin, Dimitry and Beer, Fabian and Sieger, Leonie Nora and Heindorf,
Stefan and Cimiano, Philipp and Esposito, Elena and Ngonga Ngomo, Axel-Cyrille},
year={2025} }'
chicago: 'Mindlin, Dimitry, Fabian Beer, Leonie Nora Sieger, Stefan Heindorf, Philipp
Cimiano, Elena Esposito, and Axel-Cyrille Ngonga Ngomo. “Beyond One-Shot Explanations:
A Systematic Literature Review of Dialogue-Based XAI Approaches.” Artificial
Intelligence Review 58, no. 3 (2025). https://doi.org/10.1007/s10462-024-11007-7.'
ieee: 'D. Mindlin et al., “Beyond One-Shot Explanations: A Systematic Literature
Review of Dialogue-Based XAI Approaches,” Artificial Intelligence Review,
vol. 58, no. 3, Art. no. 81, 2025, doi: 10.1007/s10462-024-11007-7.'
mla: 'Mindlin, Dimitry, et al. “Beyond One-Shot Explanations: A Systematic Literature
Review of Dialogue-Based XAI Approaches.” Artificial Intelligence Review,
vol. 58, no. 3, 81, Springer, 2025, doi:10.1007/s10462-024-11007-7.'
short: D. Mindlin, F. Beer, L.N. Sieger, S. Heindorf, P. Cimiano, E. Esposito, A.-C.
Ngonga Ngomo, Artificial Intelligence Review 58 (2025).
date_created: 2024-05-26T18:55:58Z
date_updated: 2025-01-24T20:09:20Z
department:
- _id: '760'
- _id: '574'
doi: 10.1007/s10462-024-11007-7
intvolume: ' 58'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/article/10.1007/s10462-024-11007-7
oa: '1'
publication: Artificial Intelligence Review
publication_status: published
publisher: Springer
status: public
title: 'Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based
XAI Approaches'
type: journal_article
user_id: '11871'
volume: 58
year: '2025'
...
---
_id: '61065'
abstract:
- lang: eng
text: Abduction is the task of computing a sufficient extension of a knowledge base
(KB) that entails a conclusion not entailed by the original KB. It serves to compute
explanations, or hypotheses, for such missing entailments. While this task has
been intensively investigated for perfect data and under classical semantics,
less is known about abduction when erroneous data results in inconsistent KBs.
In this paper we define a suitable notion of abduction under repair semantics
and propose a set of minimality criteria that guides abduction towards `useful'
hypotheses. We provide initial complexity results on deciding existence of and
verifying abductive solutions with these criteria, under different repair semantics
and for the description logics DL-Lite and EL_bot.
author:
- first_name: Anselm
full_name: Haak, Anselm
id: '109969'
last_name: Haak
- first_name: Patrick
full_name: Koopmann, Patrick
last_name: Koopmann
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Anni-Yasmin
full_name: Turhan, Anni-Yasmin
id: '104470'
last_name: Turhan
citation:
ama: Haak A, Koopmann P, Mahmood Y, Turhan A-Y. Why not? Developing ABox Abduction
beyond Repairs. arXiv:250721955. Published online 2025.
apa: Haak, A., Koopmann, P., Mahmood, Y., & Turhan, A.-Y. (2025). Why not? Developing
ABox Abduction beyond Repairs. In arXiv:2507.21955.
bibtex: '@article{Haak_Koopmann_Mahmood_Turhan_2025, title={Why not? Developing
ABox Abduction beyond Repairs}, journal={arXiv:2507.21955}, author={Haak, Anselm
and Koopmann, Patrick and Mahmood, Yasir and Turhan, Anni-Yasmin}, year={2025}
}'
chicago: Haak, Anselm, Patrick Koopmann, Yasir Mahmood, and Anni-Yasmin Turhan.
“Why Not? Developing ABox Abduction beyond Repairs.” ArXiv:2507.21955,
2025.
ieee: A. Haak, P. Koopmann, Y. Mahmood, and A.-Y. Turhan, “Why not? Developing ABox
Abduction beyond Repairs,” arXiv:2507.21955. 2025.
mla: Haak, Anselm, et al. “Why Not? Developing ABox Abduction beyond Repairs.” ArXiv:2507.21955,
2025.
short: A. Haak, P. Koopmann, Y. Mahmood, A.-Y. Turhan, ArXiv:2507.21955 (2025).
date_created: 2025-08-29T07:58:08Z
date_updated: 2026-02-05T13:55:48Z
department:
- _id: '574'
- _id: '888'
external_id:
arxiv:
- '2507.21955'
language:
- iso: eng
project:
- _id: '121'
name: 'TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des
maschinellen Lernens'
publication: arXiv:2507.21955
status: public
title: Why not? Developing ABox Abduction beyond Repairs
type: preprint
user_id: '109969'
year: '2025'
...
---
_id: '63888'
author:
- first_name: Anselm
full_name: Haak, Anselm
id: '109969'
last_name: Haak
- first_name: Patrick
full_name: Koopmann, Patrick
last_name: Koopmann
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Anni-Yasmin
full_name: Turhan, Anni-Yasmin
id: '104470'
last_name: Turhan
citation:
ama: 'Haak A, Koopmann P, Mahmood Y, Turhan A-Y. Why not? Developing ABox Abduction
beyond Repairs. In: Tendera L, Ibanez Garcia Y, Koopmann P, eds. Proceedings
of the 38th International Workshop on Description Logics - DL 2025. ; 2025.'
apa: Haak, A., Koopmann, P., Mahmood, Y., & Turhan, A.-Y. (2025). Why not? Developing
ABox Abduction beyond Repairs. In L. Tendera, Y. Ibanez Garcia, & P. Koopmann
(Eds.), Proceedings of the 38th International Workshop on Description Logics
- DL 2025.
bibtex: '@inproceedings{Haak_Koopmann_Mahmood_Turhan_2025, title={Why not? Developing
ABox Abduction beyond Repairs}, booktitle={Proceedings of the 38th International
Workshop on Description Logics - DL 2025}, author={Haak, Anselm and Koopmann,
Patrick and Mahmood, Yasir and Turhan, Anni-Yasmin}, editor={Tendera, Lidia and
Ibanez Garcia, Yazmin and Koopmann, Patrick}, year={2025} }'
chicago: Haak, Anselm, Patrick Koopmann, Yasir Mahmood, and Anni-Yasmin Turhan.
“Why Not? Developing ABox Abduction beyond Repairs.” In Proceedings of the
38th International Workshop on Description Logics - DL 2025, edited by Lidia
Tendera, Yazmin Ibanez Garcia, and Patrick Koopmann, 2025.
ieee: A. Haak, P. Koopmann, Y. Mahmood, and A.-Y. Turhan, “Why not? Developing ABox
Abduction beyond Repairs,” in Proceedings of the 38th International Workshop
on Description Logics - DL 2025, Opole, Poland, 2025.
mla: Haak, Anselm, et al. “Why Not? Developing ABox Abduction beyond Repairs.” Proceedings
of the 38th International Workshop on Description Logics - DL 2025, edited
by Lidia Tendera et al., 2025.
short: 'A. Haak, P. Koopmann, Y. Mahmood, A.-Y. Turhan, in: L. Tendera, Y. Ibanez
Garcia, P. Koopmann (Eds.), Proceedings of the 38th International Workshop on
Description Logics - DL 2025, 2025.'
conference:
end_date: 2025-09-06
location: Opole, Poland
name: Description Logics 2025
start_date: 2025-09-03
date_created: 2026-02-05T13:54:08Z
date_updated: 2026-02-05T13:55:27Z
department:
- _id: '888'
- _id: '574'
editor:
- first_name: Lidia
full_name: Tendera, Lidia
last_name: Tendera
- first_name: Yazmin
full_name: Ibanez Garcia, Yazmin
last_name: Ibanez Garcia
- first_name: Patrick
full_name: Koopmann, Patrick
last_name: Koopmann
language:
- iso: eng
main_file_link:
- url: https://ceur-ws.org/Vol-4091/paper25.pdf
publication: Proceedings of the 38th International Workshop on Description Logics
- DL 2025
status: public
title: Why not? Developing ABox Abduction beyond Repairs
type: conference
user_id: '109969'
year: '2025'
...
---
_id: '59910'
abstract:
- lang: eng
text: The connection between inconsistent databases and Dung’s abstract
argumentation framework has recently drawn growing interest. Specifically, an
inconsistent database, involving certain types of integrity constraints such as
functional and inclusion dependencies, can be viewed as an argumentation framework
in Dung’s setting. Nevertheless, no prior work has explored the exact expressive
power of Dung’s theory of argumentation when compared to inconsistent databases
and integrity constraints. In this paper, we close this gap by arguing that an
argumentation framework can also be viewed as an inconsistent database. We first
establish a connection between subset-repairs for databases and extensions for
AFs considering conflict-free, naive, admissible, and preferred semantics. Further,
we define a new family of attribute-based repairs based on the principle of maximal
content preservation. The effectiveness of these repairs is then highlighted by
connecting them to stable, semi-stable, and stage semantics. Our main contributions
include translating an argumentation framework into a database together with integrity
constraints. Moreover, this translation can be achieved in polynomial time, which
is essential in transferring complexity results between the two formalisms.
author:
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Markus
full_name: Hecher, Markus
last_name: Hecher
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Mahmood Y, Hecher M, Ngonga Ngomo A-C. Dung’s Argumentation Framework: Unveiling
the Expressive Power with Inconsistent Databases. In: Proceedings of the AAAI
Conference on Artificial Intelligence. Vol 39. Association for the Advancement
of Artificial Intelligence (AAAI); 2025:15058-15066. doi:10.1609/aaai.v39i14.33651'
apa: 'Mahmood, Y., Hecher, M., & Ngonga Ngomo, A.-C. (2025). Dung’s Argumentation
Framework: Unveiling the Expressive Power with Inconsistent Databases. Proceedings
of the AAAI Conference on Artificial Intelligence, 39(14), 15058–15066.
https://doi.org/10.1609/aaai.v39i14.33651'
bibtex: '@inproceedings{Mahmood_Hecher_Ngonga Ngomo_2025, title={Dung’s Argumentation
Framework: Unveiling the Expressive Power with Inconsistent Databases}, volume={39},
DOI={10.1609/aaai.v39i14.33651},
number={14}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
publisher={Association for the Advancement of Artificial Intelligence (AAAI)},
author={Mahmood, Yasir and Hecher, Markus and Ngonga Ngomo, Axel-Cyrille}, year={2025},
pages={15058–15066} }'
chicago: 'Mahmood, Yasir, Markus Hecher, and Axel-Cyrille Ngonga Ngomo. “Dung’s
Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases.”
In Proceedings of the AAAI Conference on Artificial Intelligence, 39:15058–66.
Association for the Advancement of Artificial Intelligence (AAAI), 2025. https://doi.org/10.1609/aaai.v39i14.33651.'
ieee: 'Y. Mahmood, M. Hecher, and A.-C. Ngonga Ngomo, “Dung’s Argumentation Framework:
Unveiling the Expressive Power with Inconsistent Databases,” in Proceedings
of the AAAI Conference on Artificial Intelligence, 2025, vol. 39, no. 14,
pp. 15058–15066, doi: 10.1609/aaai.v39i14.33651.'
mla: 'Mahmood, Yasir, et al. “Dung’s Argumentation Framework: Unveiling the Expressive
Power with Inconsistent Databases.” Proceedings of the AAAI Conference on Artificial
Intelligence, vol. 39, no. 14, Association for the Advancement of Artificial
Intelligence (AAAI), 2025, pp. 15058–66, doi:10.1609/aaai.v39i14.33651.'
short: 'Y. Mahmood, M. Hecher, A.-C. Ngonga Ngomo, in: Proceedings of the AAAI Conference
on Artificial Intelligence, Association for the Advancement of Artificial Intelligence
(AAAI), 2025, pp. 15058–15066.'
date_created: 2025-05-15T11:05:36Z
date_updated: 2026-02-20T10:07:00Z
department:
- _id: '574'
doi: 10.1609/aaai.v39i14.33651
intvolume: ' 39'
issue: '14'
language:
- iso: eng
page: 15058-15066
project:
- _id: '121'
name: 'TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des
maschinellen Lernens'
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
issn:
- 2374-3468
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence (AAAI)
status: public
title: 'Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent
Databases'
type: conference
user_id: '99353'
volume: 39
year: '2025'
...
---
_id: '61123'
abstract:
- lang: eng
text: Knowledge graphs are used by a growing number of applications to represent
structured data. Hence, evaluating the veracity of assertions in knowledge graphs—dubbed
fact checking—is currently a challenge of growing importance. However, manual
fact checking is commonly impractical due to the sheer size of knowledge graphs.
This paper is a systematic survey of recent works on automatic fact checking with
a focus on knowledge graphs. We present recent fact-checking approaches, the varied
sources they use as background knowledge, and the features they rely upon. Finally,
we draw conclusions pertaining to possible future research directions in fact
checking knowledge graphs.
article_number: '3749838'
article_type: original
author:
- first_name: Umair
full_name: Qudus, Umair
id: '83392'
last_name: Qudus
orcid: 0000-0001-6714-8729
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Muhammad
full_name: Saleem, Muhammad
last_name: Saleem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: Qudus U, Röder M, Saleem M, Ngonga Ngomo A-C. Fact Checking Knowledge Graphs
-- A Survey. ACM Computing Surveys. 2025;58. doi:10.1145/3749838
apa: Qudus, U., Röder, M., Saleem, M., & Ngonga Ngomo, A.-C. (2025). Fact Checking
Knowledge Graphs -- A Survey. ACM Computing Surveys, 58, Article
3749838. https://doi.org/10.1145/3749838
bibtex: '@article{Qudus_Röder_Saleem_Ngonga Ngomo_2025, title={Fact Checking Knowledge
Graphs -- A Survey}, volume={58}, DOI={10.1145/3749838},
number={3749838}, journal={ACM Computing Surveys}, publisher={Association for
Computing Machinery (ACM)}, author={Qudus, Umair and Röder, Michael and Saleem,
Muhammad and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
chicago: Qudus, Umair, Michael Röder, Muhammad Saleem, and Axel-Cyrille Ngonga Ngomo.
“Fact Checking Knowledge Graphs -- A Survey.” ACM Computing Surveys 58
(2025). https://doi.org/10.1145/3749838.
ieee: 'U. Qudus, M. Röder, M. Saleem, and A.-C. Ngonga Ngomo, “Fact Checking Knowledge
Graphs -- A Survey,” ACM Computing Surveys, vol. 58, Art. no. 3749838,
2025, doi: 10.1145/3749838.'
mla: Qudus, Umair, et al. “Fact Checking Knowledge Graphs -- A Survey.” ACM Computing
Surveys, vol. 58, 3749838, Association for Computing Machinery (ACM), 2025,
doi:10.1145/3749838.
short: U. Qudus, M. Röder, M. Saleem, A.-C. Ngonga Ngomo, ACM Computing Surveys
58 (2025).
date_created: 2025-09-03T15:46:43Z
date_updated: 2025-09-11T09:30:28Z
ddc:
- '006'
department:
- _id: '574'
doi: 10.1145/3749838
external_id:
unknown:
- 10.1145/3749838
file:
- access_level: closed
content_type: application/pdf
creator: uqudus
date_created: 2025-09-11T09:26:29Z
date_updated: 2025-09-11T09:26:29Z
file_id: '61195'
file_name: 3749838.pdf
file_size: 1062387
relation: main_file
success: 1
file_date_updated: 2025-09-11T09:26:29Z
has_accepted_license: '1'
intvolume: ' 58'
keyword:
- fact checking
- knowledge graphs
- fact-checkers
- check worthiness
- evidence retrieval
- trust
- veracity.
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/doi/pdf/10.1145/3749838
oa: '1'
popular_science: '1'
publication: ACM Computing Surveys
publication_identifier:
issn:
- 0360-0300
- 1557-7341
publication_status: published
publisher: Association for Computing Machinery (ACM)
quality_controlled: '1'
status: public
title: Fact Checking Knowledge Graphs -- A Survey
type: journal_article
user_id: '83392'
volume: 58
year: '2025'
...
---
_id: '59912'
abstract:
- lang: eng
text: "Abstract\r\n We study the
expressivity and the complexity of various logics in probabilistic team semantics
with the Boolean negation. In particular, we study the extension of probabilistic
independence logic with the Boolean negation, and a recently introduced logic
first-order theory of random variables with probabilistic independence. We give
several results that compare the expressivity of these logics with the most studied
logics in probabilistic team semantics setting, as well as relating their expressivity
to a numerical variant of second-order logic. In addition, we introduce novel
entropy atoms and show that the extension of first-order logic by entropy atoms
subsumes probabilistic independence logic. Finally, we obtain some results on
the complexity of model checking, validity and satisfiability of our logics."
author:
- first_name: Miika
full_name: Hannula, Miika
last_name: Hannula
- first_name: Minna
full_name: Hirvonen, Minna
last_name: Hirvonen
- first_name: Juha
full_name: Kontinen, Juha
last_name: Kontinen
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Arne
full_name: Meier, Arne
last_name: Meier
- first_name: Jonni
full_name: Virtema, Jonni
last_name: Virtema
citation:
ama: Hannula M, Hirvonen M, Kontinen J, Mahmood Y, Meier A, Virtema J. Logics with
probabilistic team semantics and the Boolean negation. Journal of Logic and
Computation. 2025;35(3). doi:10.1093/logcom/exaf021
apa: Hannula, M., Hirvonen, M., Kontinen, J., Mahmood, Y., Meier, A., & Virtema,
J. (2025). Logics with probabilistic team semantics and the Boolean negation.
Journal of Logic and Computation, 35(3). https://doi.org/10.1093/logcom/exaf021
bibtex: '@article{Hannula_Hirvonen_Kontinen_Mahmood_Meier_Virtema_2025, title={Logics
with probabilistic team semantics and the Boolean negation}, volume={35}, DOI={10.1093/logcom/exaf021}, number={3},
journal={Journal of Logic and Computation}, publisher={Oxford University Press
(OUP)}, author={Hannula, Miika and Hirvonen, Minna and Kontinen, Juha and Mahmood,
Yasir and Meier, Arne and Virtema, Jonni}, year={2025} }'
chicago: Hannula, Miika, Minna Hirvonen, Juha Kontinen, Yasir Mahmood, Arne Meier,
and Jonni Virtema. “Logics with Probabilistic Team Semantics and the Boolean Negation.”
Journal of Logic and Computation 35, no. 3 (2025). https://doi.org/10.1093/logcom/exaf021.
ieee: 'M. Hannula, M. Hirvonen, J. Kontinen, Y. Mahmood, A. Meier, and J. Virtema,
“Logics with probabilistic team semantics and the Boolean negation,” Journal
of Logic and Computation, vol. 35, no. 3, 2025, doi: 10.1093/logcom/exaf021.'
mla: Hannula, Miika, et al. “Logics with Probabilistic Team Semantics and the Boolean
Negation.” Journal of Logic and Computation, vol. 35, no. 3, Oxford University
Press (OUP), 2025, doi:10.1093/logcom/exaf021.
short: M. Hannula, M. Hirvonen, J. Kontinen, Y. Mahmood, A. Meier, J. Virtema, Journal
of Logic and Computation 35 (2025).
date_created: 2025-05-15T11:07:28Z
date_updated: 2025-09-11T10:00:26Z
department:
- _id: '574'
doi: 10.1093/logcom/exaf021
intvolume: ' 35'
issue: '3'
language:
- iso: eng
project:
- _id: '121'
name: 'TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des
maschinellen Lernens'
publication: Journal of Logic and Computation
publication_identifier:
issn:
- 0955-792X
- 1465-363X
publication_status: published
publisher: Oxford University Press (OUP)
status: public
title: Logics with probabilistic team semantics and the Boolean negation
type: journal_article
user_id: '99353'
volume: 35
year: '2025'
...
---
_id: '59054'
author:
- first_name: Asep Fajar
full_name: Firmansyah, Asep Fajar
id: '76787'
last_name: Firmansyah
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Mohamed
full_name: Sherif, Mohamed
id: '67234'
last_name: Sherif
orcid: https://orcid.org/0000-0002-9927-2203
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Firmansyah AF, Zahera HMA, Sherif M, Moussallem D, Ngonga Ngomo A-C. ANTS:
Abstractive Entity Summarization in Knowledge Graphs. In: ESWC2025. The
Semantic Web. pringer Nature Switzerland; 2025:133--151. doi:10.1007/978-3-031-94575-5_8'
apa: 'Firmansyah, A. F., Zahera, H. M. A., Sherif, M., Moussallem, D., & Ngonga
Ngomo, A.-C. (2025). ANTS: Abstractive Entity Summarization in Knowledge Graphs.
ESWC2025, 133--151. https://doi.org/10.1007/978-3-031-94575-5_8'
bibtex: '@inproceedings{Firmansyah_Zahera_Sherif_Moussallem_Ngonga Ngomo_2025, series={The
Semantic Web}, title={ANTS: Abstractive Entity Summarization in Knowledge Graphs},
DOI={10.1007/978-3-031-94575-5_8},
booktitle={ESWC2025}, publisher={pringer Nature Switzerland}, author={Firmansyah,
Asep Fajar and Zahera, Hamada Mohamed Abdelsamee and Sherif, Mohamed and Moussallem,
Diego and Ngonga Ngomo, Axel-Cyrille}, year={2025}, pages={133--151}, collection={The
Semantic Web} }'
chicago: 'Firmansyah, Asep Fajar, Hamada Mohamed Abdelsamee Zahera, Mohamed Sherif,
Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “ANTS: Abstractive Entity Summarization
in Knowledge Graphs.” In ESWC2025, 133--151. The Semantic Web. pringer
Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-94575-5_8.'
ieee: 'A. F. Firmansyah, H. M. A. Zahera, M. Sherif, D. Moussallem, and A.-C. Ngonga
Ngomo, “ANTS: Abstractive Entity Summarization in Knowledge Graphs,” in ESWC2025,
2025, pp. 133--151, doi: 10.1007/978-3-031-94575-5_8.'
mla: 'Firmansyah, Asep Fajar, et al. “ANTS: Abstractive Entity Summarization in
Knowledge Graphs.” ESWC2025, pringer Nature Switzerland, 2025, pp. 133--151,
doi:10.1007/978-3-031-94575-5_8.'
short: 'A.F. Firmansyah, H.M.A. Zahera, M. Sherif, D. Moussallem, A.-C. Ngonga Ngomo,
in: ESWC2025, pringer Nature Switzerland, 2025, pp. 133--151.'
conference:
name: ESWC 2025
date_created: 2025-03-17T13:41:48Z
date_updated: 2025-09-11T10:00:44Z
department:
- _id: '574'
doi: 10.1007/978-3-031-94575-5_8
keyword:
- firmansyah mousallem ngonga sherif zahera
language:
- iso: eng
page: 133--151
publication: ESWC2025
publication_identifier:
isbn:
- 978-3-031-94575-5
publication_status: published
publisher: pringer Nature Switzerland
series_title: The Semantic Web
status: public
title: 'ANTS: Abstractive Entity Summarization in Knowledge Graphs'
type: conference
user_id: '67234'
year: '2025'
...
---
_id: '61066'
abstract:
- lang: eng
text: "Argumentation is a central subarea of Artificial Intelligence (AI) for\r\nmodeling
and reasoning about arguments. The semantics of abstract argumentation\r\nframeworks
(AFs) is given by sets of arguments (extensions) and conditions on\r\nthe relationship
between them, such as stable or admissible. Today's solvers\r\nimplement tasks
such as finding extensions, deciding credulous or skeptical\r\nacceptance, counting,
or enumerating extensions. While these tasks are well\r\ncharted, the area between
decision, counting/enumeration and fine-grained\r\nreasoning requires expensive
reasoning so far. We introduce a novel concept\r\n(facets) for reasoning between
decision and enumeration. Facets are arguments\r\nthat belong to some extensions
(credulous) but not to all extensions\r\n(skeptical). They are most natural when
a user aims to navigate, filter, or\r\ncomprehend the significance of specific
arguments, according to their needs. We\r\nstudy the complexity and show that
tasks involving facets are much easier than\r\ncounting extensions. Finally, we
provide an implementation, and conduct\r\nexperiments to demonstrate feasibility."
author:
- first_name: Johannes
full_name: Fichte, Johannes
last_name: Fichte
- first_name: Nicolas
full_name: Fröhlich, Nicolas
last_name: Fröhlich
- first_name: Markus
full_name: Hecher, Markus
last_name: Hecher
- first_name: Victor
full_name: Lagerkvist, Victor
last_name: Lagerkvist
- first_name: Yasir
full_name: Mahmood, Yasir
id: '99353'
last_name: Mahmood
- first_name: Arne
full_name: Meier, Arne
last_name: Meier
- first_name: Jonathan
full_name: Persson, Jonathan
last_name: Persson
citation:
ama: 'Fichte J, Fröhlich N, Hecher M, et al. Facets in Argumentation: A Formal Approach
to Argument Significance. arXiv:250510982. Published online 2025.'
apa: 'Fichte, J., Fröhlich, N., Hecher, M., Lagerkvist, V., Mahmood, Y., Meier,
A., & Persson, J. (2025). Facets in Argumentation: A Formal Approach to Argument
Significance. In arXiv:2505.10982.'
bibtex: '@article{Fichte_Fröhlich_Hecher_Lagerkvist_Mahmood_Meier_Persson_2025,
title={Facets in Argumentation: A Formal Approach to Argument Significance}, journal={arXiv:2505.10982},
author={Fichte, Johannes and Fröhlich, Nicolas and Hecher, Markus and Lagerkvist,
Victor and Mahmood, Yasir and Meier, Arne and Persson, Jonathan}, year={2025}
}'
chicago: 'Fichte, Johannes, Nicolas Fröhlich, Markus Hecher, Victor Lagerkvist,
Yasir Mahmood, Arne Meier, and Jonathan Persson. “Facets in Argumentation: A Formal
Approach to Argument Significance.” ArXiv:2505.10982, 2025.'
ieee: 'J. Fichte et al., “Facets in Argumentation: A Formal Approach to Argument
Significance,” arXiv:2505.10982. 2025.'
mla: 'Fichte, Johannes, et al. “Facets in Argumentation: A Formal Approach to Argument
Significance.” ArXiv:2505.10982, 2025.'
short: J. Fichte, N. Fröhlich, M. Hecher, V. Lagerkvist, Y. Mahmood, A. Meier, J.
Persson, ArXiv:2505.10982 (2025).
date_created: 2025-08-29T08:07:43Z
date_updated: 2025-09-11T09:58:34Z
department:
- _id: '574'
external_id:
arxiv:
- '2505.10982'
language:
- iso: eng
project:
- _id: '121'
name: 'TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des
maschinellen Lernens'
publication: arXiv:2505.10982
status: public
title: 'Facets in Argumentation: A Formal Approach to Argument Significance'
type: preprint
user_id: '99353'
year: '2025'
...
---
_id: '61202'
abstract:
- lang: eng
text: The number of datasets on the web of data increases continuously. However,
the knowledge contained therein cannot be fully utilized without finding links
between the entities contained in these datasets. Equivalent entities can not
be identified solely by checking the equivalence of IRIs because of the different
origins and naming schemes of different data providers. Yet, such equivalences
can be discovered by computing the similarity of their attributes. In this paper
we propose GLIDE, an approach that links entities from two different datasets
by embedding a joint model of these datasets enriched by additional relations
describing the similarity of literals. The joint model is embedded into a latent
vector space while paying attention to juxtaposing similar literals. We evaluate
our approach against state-of-the-art algorithms using real-world datasets commonly
used in link discovery literature. The results show that GLIDE outperforms all
baselines on 5 of 7 datasets with perfect or near-perfect accuracy. Our approach
achieves its best performance on datasets that feature several literals with similarities.
Our experiments indicate that researchers should not only pay attention to equal
literals in knowledge graph embedding but should also be aware of the distance
between similar literals.
author:
- first_name: Alexander
full_name: Becker, Alexander
last_name: Becker
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: 'Mohamed '
full_name: 'Sherif, Mohamed '
last_name: Sherif
citation:
ama: 'Becker A, Ngonga Ngomo A-C, Sherif M. GLIDE: Knowledge Graph Linking using
Distance-Aware Embeddings. In: The Semantic Web – ISWC 2025. ; 2025.'
apa: 'Becker, A., Ngonga Ngomo, A.-C., & Sherif, M. (2025). GLIDE: Knowledge
Graph Linking using Distance-Aware Embeddings. The Semantic Web – ISWC 2025.
ISWC 2025.'
bibtex: '@inproceedings{Becker_Ngonga Ngomo_Sherif_2025, place={Nara, Japan}, title={GLIDE:
Knowledge Graph Linking using Distance-Aware Embeddings}, booktitle={The Semantic
Web – ISWC 2025}, author={Becker, Alexander and Ngonga Ngomo, Axel-Cyrille and
Sherif, Mohamed }, year={2025} }'
chicago: 'Becker, Alexander, Axel-Cyrille Ngonga Ngomo, and Mohamed Sherif. “GLIDE:
Knowledge Graph Linking Using Distance-Aware Embeddings.” In The Semantic Web
– ISWC 2025. Nara, Japan, 2025.'
ieee: 'A. Becker, A.-C. Ngonga Ngomo, and M. Sherif, “GLIDE: Knowledge Graph Linking
using Distance-Aware Embeddings,” presented at the ISWC 2025, 2025.'
mla: 'Becker, Alexander, et al. “GLIDE: Knowledge Graph Linking Using Distance-Aware
Embeddings.” The Semantic Web – ISWC 2025, 2025.'
short: 'A. Becker, A.-C. Ngonga Ngomo, M. Sherif, in: The Semantic Web – ISWC 2025,
Nara, Japan, 2025.'
conference:
name: ISWC 2025
date_created: 2025-09-11T10:04:16Z
date_updated: 2025-09-11T10:34:52Z
department:
- _id: '574'
keyword:
- becker sherif enexa sailproject dice simba ngonga whale
language:
- iso: eng
place: Nara, Japan
publication: The Semantic Web – ISWC 2025
status: public
title: 'GLIDE: Knowledge Graph Linking using Distance-Aware Embeddings'
type: conference
user_id: '67234'
year: '2025'
...
---
_id: '61134'
author:
- first_name: Ali
full_name: Manzoor, Ali
id: '77309'
last_name: Manzoor
orcid: https://orcid.org/0000-0001-8403-5160
- first_name: René
full_name: Speck, René
id: '70843'
last_name: Speck
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Muhammad
full_name: Saleem, Muhammad
last_name: Saleem
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: Manzoor A, Speck R, Zahera HMA, Saleem M, Moussallem D, Ngonga Ngomo A-C. Multilingual
Relation Extraction - A Survey. IEEE Access. Published online 2025:1-1.
doi:10.1109/access.2025.3604258
apa: Manzoor, A., Speck, R., Zahera, H. M. A., Saleem, M., Moussallem, D., &
Ngonga Ngomo, A.-C. (2025). Multilingual Relation Extraction - A Survey. IEEE
Access, 1–1. https://doi.org/10.1109/access.2025.3604258
bibtex: '@article{Manzoor_Speck_Zahera_Saleem_Moussallem_Ngonga Ngomo_2025, title={Multilingual
Relation Extraction - A Survey}, DOI={10.1109/access.2025.3604258},
journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers
(IEEE)}, author={Manzoor, Ali and Speck, René and Zahera, Hamada Mohamed Abdelsamee
and Saleem, Muhammad and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2025},
pages={1–1} }'
chicago: Manzoor, Ali, René Speck, Hamada Mohamed Abdelsamee Zahera, Muhammad Saleem,
Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “Multilingual Relation Extraction
- A Survey.” IEEE Access, 2025, 1–1. https://doi.org/10.1109/access.2025.3604258.
ieee: 'A. Manzoor, R. Speck, H. M. A. Zahera, M. Saleem, D. Moussallem, and A.-C.
Ngonga Ngomo, “Multilingual Relation Extraction - A Survey,” IEEE Access,
pp. 1–1, 2025, doi: 10.1109/access.2025.3604258.'
mla: Manzoor, Ali, et al. “Multilingual Relation Extraction - A Survey.” IEEE
Access, Institute of Electrical and Electronics Engineers (IEEE), 2025, pp.
1–1, doi:10.1109/access.2025.3604258.
short: A. Manzoor, R. Speck, H.M.A. Zahera, M. Saleem, D. Moussallem, A.-C. Ngonga
Ngomo, IEEE Access (2025) 1–1.
date_created: 2025-09-04T13:32:08Z
date_updated: 2025-09-11T11:14:27Z
department:
- _id: '574'
doi: 10.1109/access.2025.3604258
language:
- iso: eng
page: 1-1
publication: IEEE Access
publication_identifier:
issn:
- 2169-3536
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Multilingual Relation Extraction - A Survey
type: journal_article
user_id: '77309'
year: '2025'
...
---
_id: '61445'
abstract:
- lang: eng
text: ABSTRACT In recent years, there has been an increasing awareness of the importance
of incorporating diversity into research projects, focusing on both how they are
conducted and their content. Funding organizations have started to require that
research applicants pay attention to inclusion and diversity by considering gender
dimensions and other diversity factors in their project plans and ensuring gender
equality during execution. Based on an extensive literature research and expert
discussions on how to develop and implement diversity strategies in large collaborative
research projects, we argue that there is a lack of practical advice in existing
literature. Drawing from our own experiences in conceptualizing and implementing
a Diversity Program across four universities in Germany, we propose a framework
for effectively integrating diversity into collaborative research initiatives
across various academic fields.
author:
- first_name: Mariya
full_name: Lorke, Mariya
last_name: Lorke
- first_name: Rena
full_name: Amelung, Rena
last_name: Amelung
- first_name: Peter
full_name: Kuchling, Peter
last_name: Kuchling
- first_name: Benjamin
full_name: Paaßen, Benjamin
last_name: Paaßen
- first_name: Miriam
full_name: Pein-Hackelbusch, Miriam
last_name: Pein-Hackelbusch
- first_name: Franziska Margarete
full_name: Schloots, Franziska Margarete
id: '33185'
last_name: Schloots
orcid: 0009-0008-9673-2615
- first_name: Klara
full_name: Schulz, Klara
last_name: Schulz
- first_name: Annette
full_name: Nauerth, Annette
last_name: Nauerth
citation:
ama: 'Lorke M, Amelung R, Kuchling P, et al. Development and Implementation of Diversity
Programs in Large Collaborative Research Projects: An Example From Germany. Diversity
& Inclusion Research. 2025;2(4):e70040. doi:https://doi.org/10.1002/dvr2.70040'
apa: 'Lorke, M., Amelung, R., Kuchling, P., Paaßen, B., Pein-Hackelbusch, M., Schloots,
F. M., Schulz, K., & Nauerth, A. (2025). Development and Implementation of
Diversity Programs in Large Collaborative Research Projects: An Example From Germany.
Diversity & Inclusion Research, 2(4), e70040. https://doi.org/10.1002/dvr2.70040'
bibtex: '@article{Lorke_Amelung_Kuchling_Paaßen_Pein-Hackelbusch_Schloots_Schulz_Nauerth_2025,
title={Development and Implementation of Diversity Programs in Large Collaborative
Research Projects: An Example From Germany}, volume={2}, DOI={https://doi.org/10.1002/dvr2.70040},
number={4}, journal={Diversity & Inclusion Research}, author={Lorke, Mariya
and Amelung, Rena and Kuchling, Peter and Paaßen, Benjamin and Pein-Hackelbusch,
Miriam and Schloots, Franziska Margarete and Schulz, Klara and Nauerth, Annette},
year={2025}, pages={e70040} }'
chicago: 'Lorke, Mariya, Rena Amelung, Peter Kuchling, Benjamin Paaßen, Miriam Pein-Hackelbusch,
Franziska Margarete Schloots, Klara Schulz, and Annette Nauerth. “Development
and Implementation of Diversity Programs in Large Collaborative Research Projects:
An Example From Germany.” Diversity & Inclusion Research 2, no. 4 (2025):
e70040. https://doi.org/10.1002/dvr2.70040.'
ieee: 'M. Lorke et al., “Development and Implementation of Diversity Programs
in Large Collaborative Research Projects: An Example From Germany,” Diversity
& Inclusion Research, vol. 2, no. 4, p. e70040, 2025, doi: https://doi.org/10.1002/dvr2.70040.'
mla: 'Lorke, Mariya, et al. “Development and Implementation of Diversity Programs
in Large Collaborative Research Projects: An Example From Germany.” Diversity
& Inclusion Research, vol. 2, no. 4, 2025, p. e70040, doi:https://doi.org/10.1002/dvr2.70040.'
short: M. Lorke, R. Amelung, P. Kuchling, B. Paaßen, M. Pein-Hackelbusch, F.M. Schloots,
K. Schulz, A. Nauerth, Diversity & Inclusion Research 2 (2025) e70040.
date_created: 2025-09-26T07:54:16Z
date_updated: 2025-09-26T07:55:21Z
department:
- _id: '574'
doi: https://doi.org/10.1002/dvr2.70040
intvolume: ' 2'
issue: '4'
keyword:
- collaborative research projects
- diversity strategy
- gender equality
language:
- iso: eng
page: e70040
publication: Diversity & Inclusion Research
publication_status: published
status: public
title: 'Development and Implementation of Diversity Programs in Large Collaborative
Research Projects: An Example From Germany'
type: journal_article
user_id: '33185'
volume: 2
year: '2025'
...
---
_id: '61537'
author:
- first_name: Franziska Margarete
full_name: Schloots, Franziska Margarete
id: '33185'
last_name: Schloots
orcid: 0009-0008-9673-2615
citation:
ama: 'Schloots FM. Essen nach Zahlen - Die Quantifizierung von Ernährung im Alltag.
In: Jürgens JL, Lewandowski K, Aßmann S, eds. Virtuelles Essen- Interdisziplinäre
Perspektiven auf Ernährungspraktiken im digitalen Zeitalter. Virtuelle Lebenswelten.
transcript Verlag; 2025:225-251. doi:10.14361/9783839476338'
apa: Schloots, F. M. (2025). Essen nach Zahlen - Die Quantifizierung von Ernährung
im Alltag. In J. L. Jürgens, K. Lewandowski, & S. Aßmann (Eds.), Virtuelles
Essen- Interdisziplinäre Perspektiven auf Ernährungspraktiken im digitalen Zeitalter
(pp. 225–251). transcript Verlag. https://doi.org/10.14361/9783839476338
bibtex: '@inbook{Schloots_2025, place={Bielefeld}, series={Virtuelle Lebenswelten},
title={Essen nach Zahlen - Die Quantifizierung von Ernährung im Alltag}, DOI={10.14361/9783839476338}, booktitle={Virtuelles
Essen- Interdisziplinäre Perspektiven auf Ernährungspraktiken im digitalen Zeitalter},
publisher={transcript Verlag}, author={Schloots, Franziska Margarete}, editor={Jürgens,
Jane Lia and Lewandowski, Kira and Aßmann, Sandra}, year={2025}, pages={225–251},
collection={Virtuelle Lebenswelten} }'
chicago: 'Schloots, Franziska Margarete. “Essen nach Zahlen - Die Quantifizierung
von Ernährung im Alltag.” In Virtuelles Essen- Interdisziplinäre Perspektiven
auf Ernährungspraktiken im digitalen Zeitalter, edited by Jane Lia Jürgens,
Kira Lewandowski, and Sandra Aßmann, 225–51. Virtuelle Lebenswelten. Bielefeld:
transcript Verlag, 2025. https://doi.org/10.14361/9783839476338.'
ieee: 'F. M. Schloots, “Essen nach Zahlen - Die Quantifizierung von Ernährung im
Alltag,” in Virtuelles Essen- Interdisziplinäre Perspektiven auf Ernährungspraktiken
im digitalen Zeitalter, J. L. Jürgens, K. Lewandowski, and S. Aßmann, Eds.
Bielefeld: transcript Verlag, 2025, pp. 225–251.'
mla: Schloots, Franziska Margarete. “Essen nach Zahlen - Die Quantifizierung von
Ernährung im Alltag.” Virtuelles Essen- Interdisziplinäre Perspektiven auf
Ernährungspraktiken im digitalen Zeitalter, edited by Jane Lia Jürgens et
al., transcript Verlag, 2025, pp. 225–51, doi:10.14361/9783839476338.
short: 'F.M. Schloots, in: J.L. Jürgens, K. Lewandowski, S. Aßmann (Eds.), Virtuelles
Essen- Interdisziplinäre Perspektiven auf Ernährungspraktiken im digitalen Zeitalter,
transcript Verlag, Bielefeld, 2025, pp. 225–251.'
date_created: 2025-10-07T13:05:10Z
date_updated: 2025-10-07T13:05:27Z
department:
- _id: '574'
doi: 10.14361/9783839476338
editor:
- first_name: Jane Lia
full_name: Jürgens, Jane Lia
last_name: Jürgens
- first_name: Kira
full_name: Lewandowski, Kira
last_name: Lewandowski
- first_name: Sandra
full_name: Aßmann, Sandra
last_name: Aßmann
keyword:
- Selbstvermessung
- Wearables
- Diet Tracking
- Quantifizierung
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://www.transcript-verlag.de/media/pdf/d7/a7/d7/oa9783839476338.pdf
oa: '1'
page: 225-251
place: Bielefeld
publication: Virtuelles Essen- Interdisziplinäre Perspektiven auf Ernährungspraktiken
im digitalen Zeitalter
publication_identifier:
isbn:
- 978-3-8394-7633-8
publication_status: published
publisher: transcript Verlag
series_title: Virtuelle Lebenswelten
status: public
title: Essen nach Zahlen - Die Quantifizierung von Ernährung im Alltag
type: book_chapter
user_id: '33185'
year: '2025'
...
---
_id: '62119'
author:
- first_name: Reda
full_name: Ihtassine, Reda
id: '103911'
last_name: Ihtassine
- first_name: Asep Fajar
full_name: Firmansyah, Asep Fajar
id: '76787'
last_name: Firmansyah
- first_name: Nikit
full_name: Srivastava, Nikit
id: '70066'
last_name: Srivastava
orcid: 0009-0004-5164-4911
- first_name: Manzoor
full_name: Ali, Manzoor
last_name: Ali
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Mohamed
full_name: Sherif, Mohamed
id: '67234'
last_name: Sherif
orcid: https://orcid.org/0000-0002-9927-2203
citation:
ama: 'Ihtassine R, Firmansyah AF, Srivastava N, Ali M, Ngonga Ngomo A-C, Sherif
M. NL2LS: LLM-based Automatic Linking of Knowledge Graphs. In: Proceedings
of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025, The Thirteenth International
Conference on Knowledge Capture, December 10 - 12, 2025, Dayton, Ohio, USA.
ACM; 2025.'
apa: 'Ihtassine, R., Firmansyah, A. F., Srivastava, N., Ali, M., Ngonga Ngomo, A.-C.,
& Sherif, M. (2025). NL2LS: LLM-based Automatic Linking of Knowledge Graphs.
Proceedings of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025, The
Thirteenth International Conference on Knowledge Capture, December 10 - 12, 2025,
Dayton, Ohio, USA.'
bibtex: '@inproceedings{Ihtassine_Firmansyah_Srivastava_Ali_Ngonga Ngomo_Sherif_2025,
title={NL2LS: LLM-based Automatic Linking of Knowledge Graphs}, booktitle={Proceedings
of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025, The Thirteenth International
Conference on Knowledge Capture, December 10 - 12, 2025, Dayton, Ohio, USA}, publisher={ACM},
author={Ihtassine, Reda and Firmansyah, Asep Fajar and Srivastava, Nikit and Ali,
Manzoor and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed}, year={2025} }'
chicago: 'Ihtassine, Reda, Asep Fajar Firmansyah, Nikit Srivastava, Manzoor Ali,
Axel-Cyrille Ngonga Ngomo, and Mohamed Sherif. “NL2LS: LLM-Based Automatic Linking
of Knowledge Graphs.” In Proceedings of the 12th Knowledge Capture Conference
2025, {K-CAP} 2025, The Thirteenth International Conference on Knowledge Capture,
December 10 - 12, 2025, Dayton, Ohio, USA. ACM, 2025.'
ieee: 'R. Ihtassine, A. F. Firmansyah, N. Srivastava, M. Ali, A.-C. Ngonga Ngomo,
and M. Sherif, “NL2LS: LLM-based Automatic Linking of Knowledge Graphs,” 2025.'
mla: 'Ihtassine, Reda, et al. “NL2LS: LLM-Based Automatic Linking of Knowledge Graphs.”
Proceedings of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025, The
Thirteenth International Conference on Knowledge Capture, December 10 - 12, 2025,
Dayton, Ohio, USA, ACM, 2025.'
short: 'R. Ihtassine, A.F. Firmansyah, N. Srivastava, M. Ali, A.-C. Ngonga Ngomo,
M. Sherif, in: Proceedings of the 12th Knowledge Capture Conference 2025, {K-CAP}
2025, The Thirteenth International Conference on Knowledge Capture, December 10
- 12, 2025, Dayton, Ohio, USA, ACM, 2025.'
date_created: 2025-11-06T15:13:39Z
date_updated: 2025-11-06T15:19:28Z
department:
- _id: '574'
keyword:
- Srivastava ali dice enexa firmansyah ihtassine ngonga sailproject sherif whale
language:
- iso: eng
publication: Proceedings of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025,
The Thirteenth International Conference on Knowledge Capture, December 10 - 12,
2025, Dayton, Ohio, USA
publisher: ACM
status: public
title: 'NL2LS: LLM-based Automatic Linking of Knowledge Graphs'
type: conference
user_id: '76787'
year: '2025'
...
---
_id: '62701'
abstract:
- lang: eng
text: 'Learning continuous vector representations for knowledge graphs has
significantly improved state-of-the-art performances in many challenging tasks.
Yet, deep-learning-based models are only post-hoc and locally explainable. In
contrast, learning Web Ontology Language (OWL) class expressions in Description Logics (DLs) is ante-hoc and globally
explainable. However, state-of-the-art learners have two well-known lim-itations: scaling to large knowledge graphs and handling missing infor-mation. Here, we present a decision-tree-based learner (tDL) to learn
Web Ontology Languages (OWLs) class expressions over large knowl-edge
graphs, while imputing missing triples. Given positive and negative example individuals,
tDL firstly constructs unique OWL expressions in .SHOIN from concise bounded descriptions of individuals. Each OWL
class expression is used as a feature in a binary classification problem to represent
input individuals. Thereafter, tDL fits a CART decision tree to learn Boolean
decision rules distinguishing positive examples from nega-tive examples. A final
OWL expression in.SHOIN is built by traversing the built CART decision tree from the root node to leaf nodes for each
positive example. By this, tDL can learn OWL class expressions without exploration,
i.e., the number of queries to a knowledge graph is bounded by the number of input
individuals. Our empirical results show that tDL outperforms the current state-of-the-art models across
datasets. Impor-tantly, our experiments over a large knowledge graph (DBpedia
with 1.1 billion triples) show that tDL can effectively learn accurate OWL class
expressions, while the state-of-the-art models fail to return any results.
Finally, expressions learned by tDL can be seamlessly translated into
natural language explanations using a pre-trained large language model and a DL
verbalizer.'
author:
- first_name: Caglar
full_name: Demir, Caglar
last_name: Demir
- first_name: Moshood
full_name: Yekini, Moshood
last_name: Yekini
- first_name: Michael
full_name: Röder, Michael
last_name: Röder
- first_name: Yasir
full_name: Mahmood, Yasir
last_name: Mahmood
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Demir C, Yekini M, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class
Expression Learner over Large Graphs. In: Lecture Notes in Computer Science.
Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-06066-2_29'
apa: Demir, C., Yekini, M., Röder, M., Mahmood, Y., & Ngonga Ngomo, A.-C. (2025).
Tree-Based OWL Class Expression Learner over Large Graphs. In Lecture Notes
in Computer Science. European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases - ECML PKDD, Porto, Portugal.
Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-06066-2_29
bibtex: '@inbook{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham}, title={Tree-Based
OWL Class Expression Learner over Large Graphs}, DOI={10.1007/978-3-032-06066-2_29},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Demir, Caglar and Yekini, Moshood and Röder, Michael and Mahmood, Yasir
and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
chicago: 'Demir, Caglar, Moshood Yekini, Michael Röder, Yasir Mahmood, and Axel-Cyrille
Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large Graphs.” In
Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2025.
https://doi.org/10.1007/978-3-032-06066-2_29.'
ieee: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based
OWL Class Expression Learner over Large Graphs,” in Lecture Notes in Computer
Science, Cham: Springer Nature Switzerland, 2025.'
mla: Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.”
Lecture Notes in Computer Science, Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-06066-2_29.
short: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture
Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.'
conference:
end_date: 2025-09-19
location: Porto, Portugal
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases - ECML PKDD
start_date: 2025-09-15
date_created: 2025-11-28T14:09:17Z
date_updated: 2025-11-28T14:57:39Z
department:
- _id: '34'
- _id: '574'
doi: 10.1007/978-3-032-06066-2_29
keyword:
- Decision Tree
- OWL Class Expression Learning
- Description Logic
- Knowledge Graph
- Large Language Model
- Verbalizer
language:
- iso: eng
place: Cham
project:
- _id: '285'
name: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783032060655'
- '9783032060662'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Tree-Based OWL Class Expression Learner over Large Graphs
type: book_chapter
user_id: '114533'
year: '2025'
...
---
_id: '61041'
abstract:
- lang: eng
text: Large Language Models (LLMs) are increasingly deployed in real-world applications
that require access to up-to-date knowledge. However, retraining LLMs is computationally
expensive. Therefore, knowledge editing techniques are crucial for maintaining
current information and correcting erroneous assertions within pre-trained models.
Current benchmarks for knowledge editing primarily focus on recalling edited facts,
often neglecting their logical consequences. To address this limitation, we introduce
a new benchmark designed to evaluate how knowledge editing methods handle the
logical consequences of a single fact edit. Our benchmark extracts relevant logical
rules from a knowledge graph for a given edit. Then, it generates multi-hop questions
based on these rules to assess the impact on logical consequences. Our findings
indicate that while existing knowledge editing approaches can accurately insert
direct assertions into LLMs, they frequently fail to inject entailed knowledge.
Specifically, experiments with popular methods like ROME and FT reveal a substantial
performance gap, up to 24%, between evaluations on directly edited knowledge and
on entailed knowledge. This highlights the critical need for semantics-aware evaluation
frameworks in knowledge editing.
author:
- first_name: Tatiana
full_name: Moteu Ngoli, Tatiana
id: '99174'
last_name: Moteu Ngoli
- first_name: N'Dah Jean
full_name: Kouagou, N'Dah Jean
id: '87189'
last_name: Kouagou
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Moteu Ngoli T, Kouagou NJ, Zahera HMA, Ngonga Ngomo A-C. Benchmarking Knowledge
Editing using Logical Rules. In: Proceedings of the 24th International Semantic
Web Conference (ISWC 2025). Springer, Cham; 2025:pp 41-56. doi:https://doi.org/10.1007/978-3-032-09530-5_3'
apa: Moteu Ngoli, T., Kouagou, N. J., Zahera, H. M. A., & Ngonga Ngomo, A.-C.
(2025). Benchmarking Knowledge Editing using Logical Rules. Proceedings of
the 24th International Semantic Web Conference (ISWC 2025), pp 41-56. https://doi.org/10.1007/978-3-032-09530-5_3
bibtex: '@inproceedings{Moteu Ngoli_Kouagou_Zahera_Ngonga Ngomo_2025, title={Benchmarking
Knowledge Editing using Logical Rules}, DOI={https://doi.org/10.1007/978-3-032-09530-5_3},
booktitle={Proceedings of the 24th International Semantic Web Conference (ISWC
2025)}, publisher={Springer, Cham}, author={Moteu Ngoli, Tatiana and Kouagou,
N’Dah Jean and Zahera, Hamada Mohamed Abdelsamee and Ngonga Ngomo, Axel-Cyrille},
year={2025}, pages={pp 41-56} }'
chicago: Moteu Ngoli, Tatiana, N’Dah Jean Kouagou, Hamada Mohamed Abdelsamee Zahera,
and Axel-Cyrille Ngonga Ngomo. “Benchmarking Knowledge Editing Using Logical Rules.”
In Proceedings of the 24th International Semantic Web Conference (ISWC 2025),
pp 41-56. Springer, Cham, 2025. https://doi.org/10.1007/978-3-032-09530-5_3.
ieee: 'T. Moteu Ngoli, N. J. Kouagou, H. M. A. Zahera, and A.-C. Ngonga Ngomo, “Benchmarking
Knowledge Editing using Logical Rules,” in Proceedings of the 24th International
Semantic Web Conference (ISWC 2025), Nara, Japan, 2025, p. pp 41-56, doi:
https://doi.org/10.1007/978-3-032-09530-5_3.'
mla: Moteu Ngoli, Tatiana, et al. “Benchmarking Knowledge Editing Using Logical
Rules.” Proceedings of the 24th International Semantic Web Conference (ISWC
2025), Springer, Cham, 2025, p. pp 41-56, doi:https://doi.org/10.1007/978-3-032-09530-5_3.
short: 'T. Moteu Ngoli, N.J. Kouagou, H.M.A. Zahera, A.-C. Ngonga Ngomo, in: Proceedings
of the 24th International Semantic Web Conference (ISWC 2025), Springer, Cham,
2025, p. pp 41-56.'
conference:
end_date: 2025.11.6
location: Nara, Japan
name: The 24th International Semantic Web Conference (ISWC 2025)
start_date: 2025.11.2
date_created: 2025-08-27T13:17:55Z
date_updated: 2025-12-01T10:04:25Z
department:
- _id: '574'
doi: https://doi.org/10.1007/978-3-032-09530-5_3
keyword:
- dice sailproject moteu kouagou zahera ngonga
language:
- iso: eng
page: pp 41-56
project:
- _id: '285'
name: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen
publication: Proceedings of the 24th International Semantic Web Conference (ISWC 2025)
publication_identifier:
isbn:
- 978-3-032-09530-5
publication_status: published
publisher: Springer, Cham
status: public
title: Benchmarking Knowledge Editing using Logical Rules
type: conference
user_id: '99174'
year: '2025'
...
---
_id: '62007'
abstract:
- lang: eng
text: "Ensemble methods are widely employed to improve generalization in machine
learning. This has also prompted the adoption of ensemble learning for the knowledge
graph embedding (KGE) models in performing link prediction. Typical approaches
to this end train multiple models as part of the ensemble, and the diverse predictions
are then averaged. However, this approach has some significant drawbacks. For
instance, the computational overhead of training multiple models increases latency
and memory overhead. In contrast, model merging approaches offer a promising alternative
that does not require training multiple models. In this work, we introduce model
merging, specifically weighted averaging, in\r\nKGE models. Herein, a running
average of model parameters from a training epoch onward is maintained and used
for predictions. To address this, we additionally propose an approach that selectively
updates the running average of the ensemble model parameters only when the generalization
performance improves on a validation dataset. We evaluate these two different
weighted averaging approaches on link prediction tasks, comparing the state-of-the-art
benchmark ensemble approach. Additionally, we evaluate the weighted averaging
approach considering literal-augmented KGE models and multi-hop query answering
tasks as well. The results demonstrate that the proposed weighted averaging approach
consistently improves performance across diverse evaluation settings."
author:
- first_name: Rupesh
full_name: Sapkota, Rupesh
id: '89326'
last_name: Sapkota
- first_name: Caglar
full_name: Demir, Caglar
last_name: Demir
- first_name: Arnab
full_name: Sharma, Arnab
last_name: Sharma
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Sapkota R, Demir C, Sharma A, Ngonga Ngomo A-C. Parameter Averaging in Link
Prediction. In: Proceedings of the Thirteenth International Conference on Knowledge
Capture(K-CAP 2025). ACM; 2025. doi:https://doi.org/10.1145/3731443.3771365'
apa: Sapkota, R., Demir, C., Sharma, A., & Ngonga Ngomo, A.-C. (2025). Parameter
Averaging in Link Prediction. Proceedings of the Thirteenth International Conference
on Knowledge Capture(K-CAP 2025). Knowledge Capture Conference 2025, Dayton,
OH, USA. https://doi.org/10.1145/3731443.3771365
bibtex: '@inproceedings{Sapkota_Demir_Sharma_Ngonga Ngomo_2025, place={Dayton, OH,
USA}, title={Parameter Averaging in Link Prediction}, DOI={https://doi.org/10.1145/3731443.3771365},
booktitle={Proceedings of the Thirteenth International Conference on Knowledge
Capture(K-CAP 2025)}, publisher={ACM}, author={Sapkota, Rupesh and Demir, Caglar
and Sharma, Arnab and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
chicago: 'Sapkota, Rupesh, Caglar Demir, Arnab Sharma, and Axel-Cyrille Ngonga Ngomo.
“Parameter Averaging in Link Prediction.” In Proceedings of the Thirteenth
International Conference on Knowledge Capture(K-CAP 2025). Dayton, OH, USA:
ACM, 2025. https://doi.org/10.1145/3731443.3771365.'
ieee: 'R. Sapkota, C. Demir, A. Sharma, and A.-C. Ngonga Ngomo, “Parameter Averaging
in Link Prediction,” presented at the Knowledge Capture Conference 2025, Dayton,
OH, USA, 2025, doi: https://doi.org/10.1145/3731443.3771365.'
mla: Sapkota, Rupesh, et al. “Parameter Averaging in Link Prediction.” Proceedings
of the Thirteenth International Conference on Knowledge Capture(K-CAP 2025),
ACM, 2025, doi:https://doi.org/10.1145/3731443.3771365.
short: 'R. Sapkota, C. Demir, A. Sharma, A.-C. Ngonga Ngomo, in: Proceedings of
the Thirteenth International Conference on Knowledge Capture(K-CAP 2025), ACM,
Dayton, OH, USA, 2025.'
conference:
end_date: 2025-12-10
location: Dayton, OH, USA
name: Knowledge Capture Conference 2025
start_date: 2025-12-10
date_created: 2025-10-28T10:02:40Z
date_updated: 2025-12-04T09:15:07Z
ddc:
- '000'
department:
- _id: '574'
doi: https://doi.org/10.1145/3731443.3771365
file:
- access_level: open_access
content_type: application/pdf
creator: rupezzz
date_created: 2025-10-28T10:02:13Z
date_updated: 2025-10-28T10:02:13Z
file_id: '62008'
file_name: public.pdf
file_size: 837462
relation: main_file
file_date_updated: 2025-10-28T10:02:13Z
has_accepted_license: '1'
keyword:
- Knowledge Graphs
- Embeddings
- Ensemble Learning
language:
- iso: eng
main_file_link:
- url: https://papers.dice-research.org/2025/KCAP_ASWA/public.pdf
oa: '1'
place: Dayton, OH, USA
project:
- _id: '285'
name: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen
publication: Proceedings of the Thirteenth International Conference on Knowledge Capture(K-CAP
2025)
publisher: ACM
status: public
title: Parameter Averaging in Link Prediction
type: conference
user_id: '89326'
year: '2025'
...
---
_id: '63507'
author:
- first_name: Gaurav
full_name: Pandit, Gaurav
last_name: Pandit
- first_name: Michael
full_name: Röder, Michael
id: '67199'
last_name: Röder
orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Pandit G, Röder M, Ngonga Ngomo A-C. Evaluating Approximate Nearest Neighbour
Search Systems on Knowledge Graph Embeddings. In: Lecture Notes in Computer
Science. Springer Nature Switzerland; 2025. doi:10.1007/978-3-031-94575-5_4'
apa: Pandit, G., Röder, M., & Ngonga Ngomo, A.-C. (2025). Evaluating Approximate
Nearest Neighbour Search Systems on Knowledge Graph Embeddings. In Lecture
Notes in Computer Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-94575-5_4
bibtex: '@inbook{Pandit_Röder_Ngonga Ngomo_2025, place={Cham}, title={Evaluating
Approximate Nearest Neighbour Search Systems on Knowledge Graph Embeddings}, DOI={10.1007/978-3-031-94575-5_4},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Pandit, Gaurav and Röder, Michael and Ngonga Ngomo, Axel-Cyrille}, year={2025}
}'
chicago: 'Pandit, Gaurav, Michael Röder, and Axel-Cyrille Ngonga Ngomo. “Evaluating
Approximate Nearest Neighbour Search Systems on Knowledge Graph Embeddings.” In
Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2025.
https://doi.org/10.1007/978-3-031-94575-5_4.'
ieee: 'G. Pandit, M. Röder, and A.-C. Ngonga Ngomo, “Evaluating Approximate Nearest
Neighbour Search Systems on Knowledge Graph Embeddings,” in Lecture Notes in
Computer Science, Cham: Springer Nature Switzerland, 2025.'
mla: Pandit, Gaurav, et al. “Evaluating Approximate Nearest Neighbour Search Systems
on Knowledge Graph Embeddings.” Lecture Notes in Computer Science, Springer
Nature Switzerland, 2025, doi:10.1007/978-3-031-94575-5_4.
short: 'G. Pandit, M. Röder, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science,
Springer Nature Switzerland, Cham, 2025.'
date_created: 2026-01-06T09:53:58Z
date_updated: 2026-01-06T09:55:26Z
department:
- _id: '574'
- _id: '923'
doi: 10.1007/978-3-031-94575-5_4
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783031945748'
- '9783031945755'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Evaluating Approximate Nearest Neighbour Search Systems on Knowledge Graph
Embeddings
type: book_chapter
user_id: '67199'
year: '2025'
...