---
_id: '55338'
abstract:
- lang: eng
text: Metaphorical language is a pivotal element inthe realm of political framing.
Existing workfrom linguistics and the social sciences providescompelling evidence
regarding the distinctivenessof conceptual framing for politicalideology perspectives.
However, the nature andutilization of metaphors and the effect on audiencesof
different political ideologies withinpolitical discourses are hardly explored.
Toenable research in this direction, in this workwe create a dataset, originally
based on newseditorials and labeled with their persuasive effectson liberals and
conservatives and extend itwith annotations pertaining to metaphorical usageof
language. To that end, first, we identifyall single metaphors and composite metaphors.Secondly,
we provide annotations of the sourceand target domains for each metaphor. As aresult,
our corpus consists of 300 news editorialsannotated with spans of texts containingmetaphors
and the corresponding domains ofwhich these metaphors draw from. Our analysisshows
that liberal readers are affected bymetaphors, whereas conservatives are resistantto
them. Both ideologies are affected differentlybased on the metaphor source and
targetcategory. For example, liberals are affected bymetaphors in the Darkness
{&} Light (e.g., death)source domains, where as the source domain ofNature affects
conservatives more significantly.
author:
- first_name: Meghdut
full_name: Sengupta, Meghdut
id: '99459'
last_name: Sengupta
- first_name: Roxanne
full_name: El Baff, Roxanne
last_name: El Baff
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Sengupta M, El Baff R, Alshomary M, Wachsmuth H. Analyzing the Use of Metaphors
in News Editorials for Political Framing. In: Duh K, Gomez H, Bethard S, eds.
Proceedings of the 2024 Conference of the North American Chapter of the Association
for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).
Association for Computational Linguistics; 2024:3621–3631.'
apa: 'Sengupta, M., El Baff, R., Alshomary, M., & Wachsmuth, H. (2024). Analyzing
the Use of Metaphors in News Editorials for Political Framing. In K. Duh, H. Gomez,
& S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language Technologies
(Volume 1: Long Papers) (pp. 3621–3631). Association for Computational Linguistics.'
bibtex: '@inproceedings{Sengupta_El Baff_Alshomary_Wachsmuth_2024, place={Mexico
City, Mexico}, title={Analyzing the Use of Metaphors in News Editorials for Political
Framing}, booktitle={Proceedings of the 2024 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language Technologies
(Volume 1: Long Papers)}, publisher={Association for Computational Linguistics},
author={Sengupta, Meghdut and El Baff, Roxanne and Alshomary, Milad and Wachsmuth,
Henning}, editor={Duh, Kevin and Gomez, Helena and Bethard, Steven}, year={2024},
pages={3621–3631} }'
chicago: 'Sengupta, Meghdut, Roxanne El Baff, Milad Alshomary, and Henning Wachsmuth.
“Analyzing the Use of Metaphors in News Editorials for Political Framing.” In
Proceedings of the 2024 Conference of the North American Chapter of the Association
for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers),
edited by Kevin Duh, Helena Gomez, and Steven Bethard, 3621–3631. Mexico City,
Mexico: Association for Computational Linguistics, 2024.'
ieee: 'M. Sengupta, R. El Baff, M. Alshomary, and H. Wachsmuth, “Analyzing the Use
of Metaphors in News Editorials for Political Framing,” in Proceedings of the
2024 Conference of the North American Chapter of the Association for Computational
Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024, pp.
3621–3631.'
mla: 'Sengupta, Meghdut, et al. “Analyzing the Use of Metaphors in News Editorials
for Political Framing.” Proceedings of the 2024 Conference of the North American
Chapter of the Association for Computational Linguistics: Human Language Technologies
(Volume 1: Long Papers), edited by Kevin Duh et al., Association for Computational
Linguistics, 2024, pp. 3621–3631.'
short: 'M. Sengupta, R. El Baff, M. Alshomary, H. Wachsmuth, in: K. Duh, H. Gomez,
S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language Technologies
(Volume 1: Long Papers), Association for Computational Linguistics, Mexico City,
Mexico, 2024, pp. 3621–3631.'
date_created: 2024-07-22T13:08:12Z
date_updated: 2024-07-26T13:02:57Z
department:
- _id: '600'
- _id: '660'
editor:
- first_name: Kevin
full_name: Duh, Kevin
last_name: Duh
- first_name: Helena
full_name: Gomez, Helena
last_name: Gomez
- first_name: Steven
full_name: Bethard, Steven
last_name: Bethard
language:
- iso: eng
page: 3621–3631
place: Mexico City, Mexico
project:
- _id: '127'
name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens'
publication: 'Proceedings of the 2024 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language Technologies (Volume
1: Long Papers)'
publisher: Association for Computational Linguistics
status: public
title: Analyzing the Use of Metaphors in News Editorials for Political Framing
type: conference
user_id: '3900'
year: '2024'
...
---
_id: '55404'
abstract:
- lang: eng
text: Explanations are pervasive in our lives. Mostly, they occur in dialogical
form where an explainer discusses a concept or phenomenon of interest with an
explainee. Leaving the explainee with a clear understanding is not straightforward
due to the knowledge gap between the two participants. Previous research looked
at the interaction of explanation moves, dialogue acts, and topics in successful
dialogues with expert explainers. However, daily-life explanations often fail,
raising the question of what makes a dialogue successful. In this work, we study
explanation dialogues in terms of the interactions between the explainer and explainee
and how they correlate with the quality of explanations in terms of a successful
understanding on the explainee{’}s side. In particular, we first construct a corpus
of 399 dialogues from the Reddit forum {Explain Like I am Five} and annotate it
for interaction flows and explanation quality. We then analyze the interaction
flows, comparing them to those appearing in expert dialogues. Finally, we encode
the interaction flows using two language models that can handle long inputs, and
we provide empirical evidence for the effectiveness boost gained through the encoding
in predicting the success of explanation dialogues.
author:
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Felix
full_name: Lange, Felix
id: '67893'
last_name: Lange
- first_name: Meisam
full_name: Booshehri, Meisam
last_name: Booshehri
- first_name: Meghdut
full_name: Sengupta, Meghdut
id: '99459'
last_name: Sengupta
- first_name: Philipp
full_name: Cimiano, Philipp
last_name: Cimiano
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Alshomary M, Lange F, Booshehri M, Sengupta M, Cimiano P, Wachsmuth H. Modeling
the Quality of Dialogical Explanations. In: Calzolari N, Kan M-Y, Hoste V, Lenci
A, Sakti S, Xue N, eds. Proceedings of the 2024 Joint International Conference
on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024).
ELRA and ICCL; 2024:11523–11536.'
apa: Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., & Wachsmuth,
H. (2024). Modeling the Quality of Dialogical Explanations. In N. Calzolari, M.-Y.
Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the
2024 Joint International Conference on Computational Linguistics, Language Resources
and Evaluation (LREC-COLING 2024) (pp. 11523–11536). ELRA and ICCL.
bibtex: '@inproceedings{Alshomary_Lange_Booshehri_Sengupta_Cimiano_Wachsmuth_2024,
place={Torino, Italia}, title={Modeling the Quality of Dialogical Explanations},
booktitle={Proceedings of the 2024 Joint International Conference on Computational
Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}, publisher={ELRA
and ICCL}, author={Alshomary, Milad and Lange, Felix and Booshehri, Meisam and
Sengupta, Meghdut and Cimiano, Philipp and Wachsmuth, Henning}, editor={Calzolari,
Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti,
Sakriani and Xue, Nianwen}, year={2024}, pages={11523–11536} }'
chicago: 'Alshomary, Milad, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp
Cimiano, and Henning Wachsmuth. “Modeling the Quality of Dialogical Explanations.”
In Proceedings of the 2024 Joint International Conference on Computational
Linguistics, Language Resources and Evaluation (LREC-COLING 2024), edited
by Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani
Sakti, and Nianwen Xue, 11523–11536. Torino, Italia: ELRA and ICCL, 2024.'
ieee: M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, and H. Wachsmuth,
“Modeling the Quality of Dialogical Explanations,” in Proceedings of the 2024
Joint International Conference on Computational Linguistics, Language Resources
and Evaluation (LREC-COLING 2024), 2024, pp. 11523–11536.
mla: Alshomary, Milad, et al. “Modeling the Quality of Dialogical Explanations.”
Proceedings of the 2024 Joint International Conference on Computational Linguistics,
Language Resources and Evaluation (LREC-COLING 2024), edited by Nicoletta
Calzolari et al., ELRA and ICCL, 2024, pp. 11523–11536.
short: 'M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, H. Wachsmuth,
in: N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, N. Xue (Eds.), Proceedings
of the 2024 Joint International Conference on Computational Linguistics, Language
Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, Torino, Italia, 2024,
pp. 11523–11536.'
date_created: 2024-07-26T13:04:25Z
date_updated: 2024-12-17T11:30:25Z
department:
- _id: '600'
- _id: '660'
editor:
- first_name: Nicoletta
full_name: Calzolari, Nicoletta
last_name: Calzolari
- first_name: Min-Yen
full_name: Kan, Min-Yen
last_name: Kan
- first_name: Veronique
full_name: Hoste, Veronique
last_name: Hoste
- first_name: Alessandro
full_name: Lenci, Alessandro
last_name: Lenci
- first_name: Sakriani
full_name: Sakti, Sakriani
last_name: Sakti
- first_name: Nianwen
full_name: Xue, Nianwen
last_name: Xue
language:
- iso: eng
page: 11523–11536
place: Torino, Italia
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: Proceedings of the 2024 Joint International Conference on Computational
Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
publisher: ELRA and ICCL
quality_controlled: '1'
status: public
title: Modeling the Quality of Dialogical Explanations
type: conference
user_id: '67893'
year: '2024'
...
---
_id: '58722'
abstract:
- lang: eng
text: Dialects introduce syntactic and lexical variations in language that occur
in regional or social groups. Most NLP methods are not sensitive to such variations.
This may lead to unfair behavior of the methods, conveying negative bias towards
dialect speakers. While previous work has studied dialect-related fairness for
aspects like hate speech, other aspects of biased language, such as lewdness,
remain fully unexplored. To fill this gap, we investigate performance disparities
between dialects in the detection of five aspects of biased language and how to
mitigate them. To alleviate bias, we present a multitask learning approach that
models dialect language as an auxiliary task to incorporate syntactic and lexical
variations. In our experiments with African-American English dialect, we provide
empirical evidence that complementing common learning approaches with dialect
modeling improves their fairness. Furthermore, the results suggest that multitask
learning achieves state-of-the-art performance and helps to detect properties
of biased language more reliably.
author:
- first_name: Maximilian
full_name: Spliethöver, Maximilian
id: '84035'
last_name: Spliethöver
orcid: 0000-0003-4364-1409
- first_name: Sai Nikhil
full_name: Menon, Sai Nikhil
last_name: Menon
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Spliethöver M, Menon SN, Wachsmuth H. Disentangling Dialect from Social Bias
via Multitask Learning to Improve Fairness. In: Ku L-W, Martins A, Srikumar V,
eds. Findings of the Association for Computational Linguistics: ACL 2024.
Association for Computational Linguistics; 2024:9294–9313. doi:10.18653/v1/2024.findings-acl.553'
apa: 'Spliethöver, M., Menon, S. N., & Wachsmuth, H. (2024). Disentangling Dialect
from Social Bias via Multitask Learning to Improve Fairness. In L.-W. Ku, A. Martins,
& V. Srikumar (Eds.), Findings of the Association for Computational Linguistics:
ACL 2024 (pp. 9294–9313). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-acl.553'
bibtex: '@inproceedings{Spliethöver_Menon_Wachsmuth_2024, place={Bangkok, Thailand},
title={Disentangling Dialect from Social Bias via Multitask Learning to Improve
Fairness}, DOI={10.18653/v1/2024.findings-acl.553},
booktitle={Findings of the Association for Computational Linguistics: ACL 2024},
publisher={Association for Computational Linguistics}, author={Spliethöver, Maximilian
and Menon, Sai Nikhil and Wachsmuth, Henning}, editor={Ku, Lun-Wei and Martins,
Andre and Srikumar, Vivek}, year={2024}, pages={9294–9313} }'
chicago: 'Spliethöver, Maximilian, Sai Nikhil Menon, and Henning Wachsmuth. “Disentangling
Dialect from Social Bias via Multitask Learning to Improve Fairness.” In Findings
of the Association for Computational Linguistics: ACL 2024, edited by Lun-Wei
Ku, Andre Martins, and Vivek Srikumar, 9294–9313. Bangkok, Thailand: Association
for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.findings-acl.553.'
ieee: 'M. Spliethöver, S. N. Menon, and H. Wachsmuth, “Disentangling Dialect from
Social Bias via Multitask Learning to Improve Fairness,” in Findings of the
Association for Computational Linguistics: ACL 2024, 2024, pp. 9294–9313,
doi: 10.18653/v1/2024.findings-acl.553.'
mla: 'Spliethöver, Maximilian, et al. “Disentangling Dialect from Social Bias via
Multitask Learning to Improve Fairness.” Findings of the Association for Computational
Linguistics: ACL 2024, edited by Lun-Wei Ku et al., Association for Computational
Linguistics, 2024, pp. 9294–9313, doi:10.18653/v1/2024.findings-acl.553.'
short: 'M. Spliethöver, S.N. Menon, H. Wachsmuth, in: L.-W. Ku, A. Martins, V. Srikumar
(Eds.), Findings of the Association for Computational Linguistics: ACL 2024, Association
for Computational Linguistics, Bangkok, Thailand, 2024, pp. 9294–9313.'
date_created: 2025-02-20T08:18:01Z
date_updated: 2025-09-12T09:52:59Z
department:
- _id: '600'
- _id: '660'
doi: 10.18653/v1/2024.findings-acl.553
editor:
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
- first_name: Andre
full_name: Martins, Andre
last_name: Martins
- first_name: Vivek
full_name: Srikumar, Vivek
last_name: Srikumar
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aclanthology.org/2024.findings-acl.553/
oa: '1'
page: 9294–9313
place: Bangkok, Thailand
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: 'Findings of the Association for Computational Linguistics: ACL 2024'
publisher: Association for Computational Linguistics
related_material:
link:
- relation: software
url: https://github.com/webis-de/acl24-dialect-aware-bias-detection
status: public
title: Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
type: conference
user_id: '84035'
year: '2024'
...
---
_id: '55406'
abstract:
- lang: eng
text: Metaphorical language, such as {“}spending time together{”}, projects meaning
from a source domain (here, $money$) to a target domain ($time$). Thereby, it
highlights certain aspects of the target domain, such as the $effort$ behind the
time investment. Highlighting aspects with metaphors (while hiding others) bridges
the two domains and is the core of metaphorical meaning construction. For metaphor
interpretation, linguistic theories stress that identifying the highlighted aspects
is important for a better understanding of metaphors. However, metaphor research
in NLP has not yet dealt with the phenomenon of highlighting. In this paper, we
introduce the task of identifying the main aspect highlighted in a metaphorical
sentence. Given the inherent interaction of source domains and highlighted aspects,
we propose two multitask approaches - a joint learning approach and a continual
learning approach - based on a finetuned contrastive learning model to jointly
predict highlighted aspects and source domains. We further investigate whether
(predicted) information about a source domain leads to better performance in predicting
the highlighted aspects, and vice versa. Our experiments on an existing corpus
suggest that, with the corresponding information, the performance to predict the
other improves in terms of model accuracy in predicting highlighted aspects and
source domains notably compared to the single-task baselines.
author:
- first_name: Meghdut
full_name: Sengupta, Meghdut
id: '99459'
last_name: Sengupta
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Sengupta M, Alshomary M, Scharlau I, Wachsmuth H. Modeling Highlighting of
Metaphors in Multitask Contrastive Learning Paradigms. In: Bouamor H, Pino J,
Bali K, eds. Findings of the Association for Computational Linguistics: EMNLP
2023. Association for Computational Linguistics; 2023:4636–4659. doi:10.18653/v1/2023.findings-emnlp.308'
apa: 'Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling
Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In H. Bouamor,
J. Pino, & K. Bali (Eds.), Findings of the Association for Computational
Linguistics: EMNLP 2023 (pp. 4636–4659). Association for Computational Linguistics.
https://doi.org/10.18653/v1/2023.findings-emnlp.308'
bibtex: '@inproceedings{Sengupta_Alshomary_Scharlau_Wachsmuth_2023, place={Singapore},
title={Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms},
DOI={10.18653/v1/2023.findings-emnlp.308},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
publisher={Association for Computational Linguistics}, author={Sengupta, Meghdut
and Alshomary, Milad and Scharlau, Ingrid and Wachsmuth, Henning}, editor={Bouamor,
Houda and Pino, Juan and Bali, Kalika}, year={2023}, pages={4636–4659} }'
chicago: 'Sengupta, Meghdut, Milad Alshomary, Ingrid Scharlau, and Henning Wachsmuth.
“Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms.”
In Findings of the Association for Computational Linguistics: EMNLP 2023,
edited by Houda Bouamor, Juan Pino, and Kalika Bali, 4636–4659. Singapore: Association
for Computational Linguistics, 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.308.'
ieee: 'M. Sengupta, M. Alshomary, I. Scharlau, and H. Wachsmuth, “Modeling Highlighting
of Metaphors in Multitask Contrastive Learning Paradigms,” in Findings of the
Association for Computational Linguistics: EMNLP 2023, 2023, pp. 4636–4659,
doi: 10.18653/v1/2023.findings-emnlp.308.'
mla: 'Sengupta, Meghdut, et al. “Modeling Highlighting of Metaphors in Multitask
Contrastive Learning Paradigms.” Findings of the Association for Computational
Linguistics: EMNLP 2023, edited by Houda Bouamor et al., Association for Computational
Linguistics, 2023, pp. 4636–4659, doi:10.18653/v1/2023.findings-emnlp.308.'
short: 'M. Sengupta, M. Alshomary, I. Scharlau, H. Wachsmuth, in: H. Bouamor, J.
Pino, K. Bali (Eds.), Findings of the Association for Computational Linguistics:
EMNLP 2023, Association for Computational Linguistics, Singapore, 2023, pp. 4636–4659.'
date_created: 2024-07-26T13:09:20Z
date_updated: 2024-07-26T13:19:53Z
department:
- _id: '600'
- _id: '660'
doi: 10.18653/v1/2023.findings-emnlp.308
editor:
- first_name: Houda
full_name: Bouamor, Houda
last_name: Bouamor
- first_name: Juan
full_name: Pino, Juan
last_name: Pino
- first_name: Kalika
full_name: Bali, Kalika
last_name: Bali
language:
- iso: eng
page: 4636–4659
place: Singapore
project:
- _id: '127'
name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens'
publication: 'Findings of the Association for Computational Linguistics: EMNLP 2023'
publisher: Association for Computational Linguistics
status: public
title: Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms
type: conference
user_id: '3900'
year: '2023'
...
---
_id: '58723'
abstract:
- lang: eng
text: In real-world debates, the most common way to counter an argument is to reason
against its main point, that is, its conclusion. Existing work on the automatic
generation of natural language counter-arguments does not address the relation
to the conclusion, possibly because many arguments leave their conclusion implicit.
In this paper, we hypothesize that the key to effective counter-argument generation
is to explicitly model the argument‘s conclusion and to ensure that the stance
of the generated counter is opposite to that conclusion. In particular, we propose
a multitask approach that jointly learns to generate both the conclusion and the
counter of an input argument. The approach employs a stance-based ranking component
that selects the counter from a diverse set of generated candidates whose stance
best opposes the generated conclusion. In both automatic and manual evaluation,
we provide evidence that our approach generates more relevant and stance-adhering
counters than strong baselines.
author:
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Alshomary M, Wachsmuth H. Conclusion-based Counter-Argument Generation. In:
Vlachos A, Augenstein I, eds. Proceedings of the 17th Conference of the European
Chapter of the Association for Computational Linguistics. Association for
Computational Linguistics; 2023:957–967. doi:10.18653/v1/2023.eacl-main.67'
apa: Alshomary, M., & Wachsmuth, H. (2023). Conclusion-based Counter-Argument
Generation. In A. Vlachos & I. Augenstein (Eds.), Proceedings of the 17th
Conference of the European Chapter of the Association for Computational Linguistics
(pp. 957–967). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.eacl-main.67
bibtex: '@inproceedings{Alshomary_Wachsmuth_2023, place={Dubrovnik, Croatia}, title={Conclusion-based
Counter-Argument Generation}, DOI={10.18653/v1/2023.eacl-main.67},
booktitle={Proceedings of the 17th Conference of the European Chapter of the Association
for Computational Linguistics}, publisher={Association for Computational Linguistics},
author={Alshomary, Milad and Wachsmuth, Henning}, editor={Vlachos, Andreas and
Augenstein, Isabelle}, year={2023}, pages={957–967} }'
chicago: 'Alshomary, Milad, and Henning Wachsmuth. “Conclusion-Based Counter-Argument
Generation.” In Proceedings of the 17th Conference of the European Chapter
of the Association for Computational Linguistics, edited by Andreas Vlachos
and Isabelle Augenstein, 957–967. Dubrovnik, Croatia: Association for Computational
Linguistics, 2023. https://doi.org/10.18653/v1/2023.eacl-main.67.'
ieee: 'M. Alshomary and H. Wachsmuth, “Conclusion-based Counter-Argument Generation,”
in Proceedings of the 17th Conference of the European Chapter of the Association
for Computational Linguistics, 2023, pp. 957–967, doi: 10.18653/v1/2023.eacl-main.67.'
mla: Alshomary, Milad, and Henning Wachsmuth. “Conclusion-Based Counter-Argument
Generation.” Proceedings of the 17th Conference of the European Chapter of
the Association for Computational Linguistics, edited by Andreas Vlachos and
Isabelle Augenstein, Association for Computational Linguistics, 2023, pp. 957–967,
doi:10.18653/v1/2023.eacl-main.67.
short: 'M. Alshomary, H. Wachsmuth, in: A. Vlachos, I. Augenstein (Eds.), Proceedings
of the 17th Conference of the European Chapter of the Association for Computational
Linguistics, Association for Computational Linguistics, Dubrovnik, Croatia, 2023,
pp. 957–967.'
date_created: 2025-02-20T08:20:35Z
date_updated: 2025-02-20T08:21:41Z
department:
- _id: '600'
- _id: '660'
doi: 10.18653/v1/2023.eacl-main.67
editor:
- first_name: Andreas
full_name: Vlachos, Andreas
last_name: Vlachos
- first_name: Isabelle
full_name: Augenstein, Isabelle
last_name: Augenstein
language:
- iso: eng
page: 957–967
place: Dubrovnik, Croatia
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: Proceedings of the 17th Conference of the European Chapter of the Association
for Computational Linguistics
publisher: Association for Computational Linguistics
status: public
title: Conclusion-based Counter-Argument Generation
type: conference
user_id: '3900'
year: '2023'
...
---
_id: '33004'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
citation:
ama: 'Wachsmuth H, Alshomary M. “Mama Always Had a Way of Explaining Things So I
Could Understand”: A Dialogue Corpus for Learning How to Explain. In: Proceedings
of the 29th International Conference on Computational Linguistics. ; 2022:344-354.'
apa: 'Wachsmuth, H., & Alshomary, M. (2022). “Mama Always Had a Way of Explaining
Things So I Could Understand”: A Dialogue Corpus for Learning How to Explain.
Proceedings of the 29th International Conference on Computational Linguistics,
344–354.'
bibtex: '@inproceedings{Wachsmuth_Alshomary_2022, title={“Mama Always Had a Way
of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning How
to Explain}, booktitle={Proceedings of the 29th International Conference on Computational
Linguistics}, author={Wachsmuth, Henning and Alshomary, Milad}, year={2022}, pages={344–354}
}'
chicago: 'Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining
Things So I Could Understand’: A Dialogue Corpus for Learning How to Explain.”
In Proceedings of the 29th International Conference on Computational Linguistics,
344–54, 2022.'
ieee: 'H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things
So I Could Understand’: A Dialogue Corpus for Learning How to Explain,” in Proceedings
of the 29th International Conference on Computational Linguistics, 2022, pp.
344–354.'
mla: 'Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining
Things So I Could Understand’: A Dialogue Corpus for Learning How to Explain.”
Proceedings of the 29th International Conference on Computational Linguistics,
2022, pp. 344–54.'
short: 'H. Wachsmuth, M. Alshomary, in: Proceedings of the 29th International Conference
on Computational Linguistics, 2022, pp. 344–354.'
date_created: 2022-08-18T10:00:46Z
date_updated: 2022-11-10T09:06:39Z
department:
- _id: '600'
language:
- iso: eng
page: 344 - 354
publication: Proceedings of the 29th International Conference on Computational Linguistics
status: public
title: '"Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue
Corpus for Learning How to Explain'
type: conference
user_id: '82920'
year: '2022'
...
---
_id: '34049'
author:
- first_name: Anne
full_name: Lauscher, Anne
last_name: Lauscher
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Iryna
full_name: Gurevych, Iryna
last_name: Gurevych
- first_name: Goran
full_name: Glavaš, Goran
last_name: Glavaš
citation:
ama: Lauscher A, Wachsmuth H, Gurevych I, Glavaš G. On the Role of Knowledge in
Computational Argumentation. Transactions of the Association for Computational
Linguistics. Published online 2022.
apa: Lauscher, A., Wachsmuth, H., Gurevych, I., & Glavaš, G. (2022). On the
Role of Knowledge in Computational Argumentation. Transactions of the Association
for Computational Linguistics.
bibtex: '@article{Lauscher_Wachsmuth_Gurevych_Glavaš_2022, title={On the Role of
Knowledge in Computational Argumentation}, journal={Transactions of the Association
for Computational Linguistics}, author={Lauscher, Anne and Wachsmuth, Henning
and Gurevych, Iryna and Glavaš, Goran}, year={2022} }'
chicago: Lauscher, Anne, Henning Wachsmuth, Iryna Gurevych, and Goran Glavaš. “On
the Role of Knowledge in Computational Argumentation.” Transactions of the
Association for Computational Linguistics, 2022.
ieee: A. Lauscher, H. Wachsmuth, I. Gurevych, and G. Glavaš, “On the Role of Knowledge
in Computational Argumentation,” Transactions of the Association for Computational
Linguistics, 2022.
mla: Lauscher, Anne, et al. “On the Role of Knowledge in Computational Argumentation.”
Transactions of the Association for Computational Linguistics, 2022.
short: A. Lauscher, H. Wachsmuth, I. Gurevych, G. Glavaš, Transactions of the Association
for Computational Linguistics (2022).
date_created: 2022-11-10T08:39:38Z
date_updated: 2022-11-10T08:39:48Z
department:
- _id: '600'
language:
- iso: eng
publication: Transactions of the Association for Computational Linguistics
status: public
title: On the Role of Knowledge in Computational Argumentation
type: journal_article
user_id: '82920'
year: '2022'
...
---
_id: '22157'
author:
- first_name: Johannes
full_name: Kiesel, Johannes
last_name: Kiesel
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Nicolas
full_name: Handke, Nicolas
last_name: Handke
- first_name: Xiaoni
full_name: Cai, Xiaoni
last_name: Cai
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
citation:
ama: 'Kiesel J, Alshomary M, Handke N, Cai X, Wachsmuth H, Stein B. Identifying
the Human Values behind Arguments. In: Proceedings of the 60th Annual Meeting
of the Association for Computational Linguistics. ; 2022:4459-4471.'
apa: Kiesel, J., Alshomary, M., Handke, N., Cai, X., Wachsmuth, H., & Stein,
B. (2022). Identifying the Human Values behind Arguments. Proceedings of the
60th Annual Meeting of the Association for Computational Linguistics, 4459–4471.
bibtex: '@inproceedings{Kiesel_Alshomary_Handke_Cai_Wachsmuth_Stein_2022, title={Identifying
the Human Values behind Arguments}, booktitle={Proceedings of the 60th Annual
Meeting of the Association for Computational Linguistics}, author={Kiesel, Johannes
and Alshomary, Milad and Handke, Nicolas and Cai, Xiaoni and Wachsmuth, Henning
and Stein, Benno}, year={2022}, pages={4459–4471} }'
chicago: Kiesel, Johannes, Milad Alshomary, Nicolas Handke, Xiaoni Cai, Henning
Wachsmuth, and Benno Stein. “Identifying the Human Values behind Arguments.” In
Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics, 4459–71, 2022.
ieee: J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, and B. Stein, “Identifying
the Human Values behind Arguments,” in Proceedings of the 60th Annual Meeting
of the Association for Computational Linguistics, 2022, pp. 4459–4471.
mla: Kiesel, Johannes, et al. “Identifying the Human Values behind Arguments.” Proceedings
of the 60th Annual Meeting of the Association for Computational Linguistics,
2022, pp. 4459–71.
short: 'J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, B. Stein, in:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics,
2022, pp. 4459–4471.'
date_created: 2021-05-11T23:15:42Z
date_updated: 2022-11-10T09:09:27Z
department:
- _id: '600'
language:
- iso: eng
page: 4459 - 4471
publication: Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics
status: public
title: Identifying the Human Values behind Arguments
type: conference
user_id: '82920'
year: '2022'
...
---
_id: '34047'
abstract:
- lang: eng
text: "News articles both shape and reflect public opinion across the political\r\nspectrum.
Analyzing them for social bias can thus provide valuable insights,\r\nsuch as
prevailing stereotypes in society and the media, which are often\r\nadopted by
NLP models trained on respective data. Recent work has relied on\r\nword embedding
bias measures, such as WEAT. However, several representation\r\nissues of embeddings
can harm the measures' accuracy, including low-resource\r\nsettings and token
frequency differences. In this work, we study what kind of\r\nembedding algorithm
serves best to accurately measure types of social bias\r\nknown to exist in US
online news articles. To cover the whole spectrum of\r\npolitical bias in the
US, we collect 500k articles and review psychology\r\nliterature with respect
to expected social bias. We then quantify social bias\r\nusing WEAT along with
embedding algorithms that account for the aforementioned\r\nissues. We compare
how models trained with the algorithms on news articles\r\nrepresent the expected
social bias. Our results suggest that the standard way\r\nto quantify bias does
not align well with knowledge from psychology. While the\r\nproposed algorithms
reduce the~gap, they still do not fully match the\r\nliterature."
author:
- first_name: Maximilian
full_name: Spliethöver, Maximilian
last_name: Spliethöver
- first_name: Maximilian
full_name: Keiff, Maximilian
last_name: Keiff
- first_name: Henning
full_name: Wachsmuth, Henning
last_name: Wachsmuth
citation:
ama: 'Spliethöver M, Keiff M, Wachsmuth H. No Word Embedding Model Is Perfect: Evaluating
the Representation Accuracy for Social Bias in the Media. In: Proceedings
of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP
2022). Association for Computational Linguistics; 2022.'
apa: 'Spliethöver, M., Keiff, M., & Wachsmuth, H. (2022). No Word Embedding
Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the
Media. Proceedings of The 2022 Conference on Empirical Methods in Natural Language
Processing (EMNLP 2022). The 2022 Conference on Empirical Methods in Natural
Language Processing (EMNLP 2022), Abu Dhabi.'
bibtex: '@inproceedings{Spliethöver_Keiff_Wachsmuth_2022, title={No Word Embedding
Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the
Media}, booktitle={Proceedings of The 2022 Conference on Empirical Methods in
Natural Language Processing (EMNLP 2022)}, publisher={Association for Computational
Linguistics}, author={Spliethöver, Maximilian and Keiff, Maximilian and Wachsmuth,
Henning}, year={2022} }'
chicago: 'Spliethöver, Maximilian, Maximilian Keiff, and Henning Wachsmuth. “No
Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social
Bias in the Media.” In Proceedings of The 2022 Conference on Empirical Methods
in Natural Language Processing (EMNLP 2022). Association for Computational
Linguistics, 2022.'
ieee: 'M. Spliethöver, M. Keiff, and H. Wachsmuth, “No Word Embedding Model Is Perfect:
Evaluating the Representation Accuracy for Social Bias in the Media,” presented
at the The 2022 Conference on Empirical Methods in Natural Language Processing
(EMNLP 2022), Abu Dhabi, 2022.'
mla: 'Spliethöver, Maximilian, et al. “No Word Embedding Model Is Perfect: Evaluating
the Representation Accuracy for Social Bias in the Media.” Proceedings of
The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP
2022), Association for Computational Linguistics, 2022.'
short: 'M. Spliethöver, M. Keiff, H. Wachsmuth, in: Proceedings of The 2022 Conference
on Empirical Methods in Natural Language Processing (EMNLP 2022), Association
for Computational Linguistics, 2022.'
conference:
end_date: 2022-12-11
location: Abu Dhabi
name: The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP
2022)
start_date: 2022-12-07
date_created: 2022-11-10T08:28:53Z
date_updated: 2022-11-11T12:49:47Z
department:
- _id: '600'
extern: '1'
external_id:
arxiv:
- '2211.03634'
language:
- iso: eng
publication: Proceedings of The 2022 Conference on Empirical Methods in Natural Language
Processing (EMNLP 2022)
publisher: Association for Computational Linguistics
status: public
title: 'No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy
for Social Bias in the Media'
type: conference
user_id: '84035'
year: '2022'
...
---
_id: '34077'
alternative_title:
- Extended Abstract
author:
- first_name: Alexander
full_name: Bondarenko, Alexander
last_name: Bondarenko
- first_name: Maik
full_name: Fröbe, Maik
last_name: Fröbe
- first_name: Johannes
full_name: Kiesel, Johannes
last_name: Kiesel
- first_name: Shahbaz
full_name: Syed, Shahbaz
last_name: Syed
- first_name: Timon
full_name: Gurcke, Timon
last_name: Gurcke
- first_name: Meriem
full_name: Beloucif, Meriem
last_name: Beloucif
- first_name: Alexander
full_name: Panchenko, Alexander
last_name: Panchenko
- first_name: Chris
full_name: Biemann, Chris
last_name: Biemann
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Henning
full_name: Wachsmuth, Henning
last_name: Wachsmuth
- first_name: Martin
full_name: Potthast, Martin
last_name: Potthast
- first_name: Matthias
full_name: Hagen, Matthias
last_name: Hagen
citation:
ama: 'Bondarenko A, Fröbe M, Kiesel J, et al. Overview of Touché 2022: Argument
Retrieval. In: Lecture Notes in Computer Science. Springer International
Publishing; 2022. doi:10.1007/978-3-030-99739-7_43'
apa: 'Bondarenko, A., Fröbe, M., Kiesel, J., Syed, S., Gurcke, T., Beloucif, M.,
Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., Potthast, M., & Hagen,
M. (2022). Overview of Touché 2022: Argument Retrieval. In Lecture Notes in
Computer Science. Springer International Publishing. https://doi.org/10.1007/978-3-030-99739-7_43'
bibtex: '@inbook{Bondarenko_Fröbe_Kiesel_Syed_Gurcke_Beloucif_Panchenko_Biemann_Stein_Wachsmuth_et
al._2022, place={Cham}, title={Overview of Touché 2022: Argument Retrieval}, DOI={10.1007/978-3-030-99739-7_43},
booktitle={Lecture Notes in Computer Science}, publisher={Springer International
Publishing}, author={Bondarenko, Alexander and Fröbe, Maik and Kiesel, Johannes
and Syed, Shahbaz and Gurcke, Timon and Beloucif, Meriem and Panchenko, Alexander
and Biemann, Chris and Stein, Benno and Wachsmuth, Henning and et al.}, year={2022}
}'
chicago: 'Bondarenko, Alexander, Maik Fröbe, Johannes Kiesel, Shahbaz Syed, Timon
Gurcke, Meriem Beloucif, Alexander Panchenko, et al. “Overview of Touché 2022:
Argument Retrieval.” In Lecture Notes in Computer Science. Cham: Springer
International Publishing, 2022. https://doi.org/10.1007/978-3-030-99739-7_43.'
ieee: 'A. Bondarenko et al., “Overview of Touché 2022: Argument Retrieval,”
in Lecture Notes in Computer Science, Cham: Springer International Publishing,
2022.'
mla: 'Bondarenko, Alexander, et al. “Overview of Touché 2022: Argument Retrieval.”
Lecture Notes in Computer Science, Springer International Publishing, 2022,
doi:10.1007/978-3-030-99739-7_43.'
short: 'A. Bondarenko, M. Fröbe, J. Kiesel, S. Syed, T. Gurcke, M. Beloucif, A.
Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Lecture
Notes in Computer Science, Springer International Publishing, Cham, 2022.'
date_created: 2022-11-14T13:47:51Z
date_updated: 2022-11-14T13:48:38Z
department:
- _id: '600'
doi: 10.1007/978-3-030-99739-7_43
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783030997380'
- '9783030997397'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
status: public
title: 'Overview of Touché 2022: Argument Retrieval'
type: book_chapter
user_id: '52174'
year: '2022'
...
---
_id: '33274'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Garima
full_name: Mudgal, Garima
last_name: Mudgal
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument
Structures in Learner Essays. In: Proceedings of the 9th Workshop on Argument
Mining (ArgMining 2022). ; 2022:51-61.'
apa: Chen, W.-F., Chen, M.-H., Mudgal, G., & Wachsmuth, H. (2022). Analyzing
Culture-Specific Argument Structures in Learner Essays. Proceedings of the
9th Workshop on Argument Mining (ArgMining 2022), 51–61.
bibtex: '@inproceedings{Chen_Chen_Mudgal_Wachsmuth_2022, title={Analyzing Culture-Specific
Argument Structures in Learner Essays}, booktitle={Proceedings of the 9th Workshop
on Argument Mining (ArgMining 2022)}, author={Chen, Wei-Fan and Chen, Mei-Hua
and Mudgal, Garima and Wachsmuth, Henning}, year={2022}, pages={51–61} }'
chicago: Chen, Wei-Fan, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. “Analyzing
Culture-Specific Argument Structures in Learner Essays.” In Proceedings of
the 9th Workshop on Argument Mining (ArgMining 2022), 51–61, 2022.
ieee: W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific
Argument Structures in Learner Essays,” in Proceedings of the 9th Workshop
on Argument Mining (ArgMining 2022), 2022, pp. 51–61.
mla: Chen, Wei-Fan, et al. “Analyzing Culture-Specific Argument Structures in Learner
Essays.” Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022),
2022, pp. 51–61.
short: 'W.-F. Chen, M.-H. Chen, G. Mudgal, H. Wachsmuth, in: Proceedings of the
9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.'
date_created: 2022-09-06T13:51:23Z
date_updated: 2022-11-18T09:56:17Z
department:
- _id: '600'
language:
- iso: eng
page: 51 - 61
project:
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
publication: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)
status: public
title: Analyzing Culture-Specific Argument Structures in Learner Essays
type: conference
user_id: '477'
year: '2022'
...
---
_id: '31068'
author:
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Garima
full_name: Mudgal, Garima
last_name: Mudgal
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Chen M-H, Mudgal G, Chen W-F, Wachsmuth H. Investigating the argumentation
structures of EFL learners from diverse language backgrounds. In: EUROCALL.
; 2022.'
apa: Chen, M.-H., Mudgal, G., Chen, W.-F., & Wachsmuth, H. (2022). Investigating
the argumentation structures of EFL learners from diverse language backgrounds.
EUROCALL.
bibtex: '@inproceedings{Chen_Mudgal_Chen_Wachsmuth_2022, title={Investigating the
argumentation structures of EFL learners from diverse language backgrounds}, booktitle={EUROCALL},
author={Chen, Mei-Hua and Mudgal, Garima and Chen, Wei-Fan and Wachsmuth, Henning},
year={2022} }'
chicago: Chen, Mei-Hua, Garima Mudgal, Wei-Fan Chen, and Henning Wachsmuth. “Investigating
the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.”
In EUROCALL, 2022.
ieee: M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation
structures of EFL learners from diverse language backgrounds,” 2022.
mla: Chen, Mei-Hua, et al. “Investigating the Argumentation Structures of EFL Learners
from Diverse Language Backgrounds.” EUROCALL, 2022.
short: 'M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.'
date_created: 2022-05-05T07:50:21Z
date_updated: 2022-05-09T14:58:39Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication: EUROCALL
status: public
title: Investigating the argumentation structures of EFL learners from diverse language
backgrounds
type: conference_abstract
user_id: '82920'
year: '2022'
...
---
_id: '55337'
abstract:
- lang: eng
text: As AI is more and more pervasive in everyday life, humans have an increasing
demand to understand its behavior and decisions. Most research on explainable
AI builds on the premise that there is one ideal explanation to be found. In fact,
however, everyday explanations are co-constructed in a dialogue between the person
explaining (the explainer) and the specific person being explained to (the explainee).
In this paper, we introduce a first corpus of dialogical explanations to enable
NLP research on how humans explain as well as on how AI can learn to imitate this
process. The corpus consists of 65 transcribed English dialogues from the Wired
video series 5 Levels, explaining 13 topics to five explainees of different proficiency.
All 1550 dialogue turns have been manually labeled by five independent professionals
for the topic discussed as well as for the dialogue act and the explanation move
performed. We analyze linguistic patterns of explainers and explainees, and we
explore differences across proficiency levels. BERT-based baseline results indicate
that sequence information helps predicting topics, acts, and moves effectively.
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
citation:
ama: 'Wachsmuth H, Alshomary M. “Mama Always Had a Way of Explaining Things So I
Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In:
Calzolari N, Huang C-R, Kim H, et al., eds. Proceedings of the 29th International
Conference on Computational Linguistics. International Committee on Computational
Linguistics; 2022:344–354.'
apa: 'Wachsmuth, H., & Alshomary, M. (2022). “Mama Always Had a Way of Explaining
Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations.
In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M.
Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim,
Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, & S.-H. Na (Eds.), Proceedings
of the 29th International Conference on Computational Linguistics (pp. 344–354).
International Committee on Computational Linguistics.'
bibtex: '@inproceedings{Wachsmuth_Alshomary_2022, place={Gyeongju, Republic of Korea},
title={“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue
Corpus for Learning to Construct Explanations}, booktitle={Proceedings of the
29th International Conference on Computational Linguistics}, publisher={International
Committee on Computational Linguistics}, author={Wachsmuth, Henning and Alshomary,
Milad}, editor={Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky,
James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and
Donatelli, Lucia and Ji, Heng and et al.}, year={2022}, pages={344–354} }'
chicago: 'Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining
Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations.”
In Proceedings of the 29th International Conference on Computational Linguistics,
edited by Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky,
Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, et al., 344–354. Gyeongju, Republic of Korea:
International Committee on Computational Linguistics, 2022.'
ieee: 'H. Wachsmuth and M. Alshomary, “‘Mama Always Had a Way of Explaining Things
So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations,”
in Proceedings of the 29th International Conference on Computational Linguistics,
2022, pp. 344–354.'
mla: 'Wachsmuth, Henning, and Milad Alshomary. “‘Mama Always Had a Way of Explaining
Things So I Could Understand’: A Dialogue Corpus for Learning to Construct Explanations.”
Proceedings of the 29th International Conference on Computational Linguistics,
edited by Nicoletta Calzolari et al., International Committee on Computational
Linguistics, 2022, pp. 344–354.'
short: 'H. Wachsmuth, M. Alshomary, in: N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky,
L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi,
P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T.K. Lee, E. Santus, F. Bond, S.-H.
Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics,
International Committee on Computational Linguistics, Gyeongju, Republic of Korea,
2022, pp. 344–354.'
date_created: 2024-07-22T13:05:42Z
date_updated: 2024-07-26T13:05:45Z
department:
- _id: '600'
- _id: '660'
editor:
- first_name: Nicoletta
full_name: Calzolari, Nicoletta
last_name: Calzolari
- first_name: Chu-Ren
full_name: Huang, Chu-Ren
last_name: Huang
- first_name: Hansaem
full_name: Kim, Hansaem
last_name: Kim
- first_name: James
full_name: Pustejovsky, James
last_name: Pustejovsky
- first_name: Leo
full_name: Wanner, Leo
last_name: Wanner
- first_name: Key-Sun
full_name: Choi, Key-Sun
last_name: Choi
- first_name: Pum-Mo
full_name: Ryu, Pum-Mo
last_name: Ryu
- first_name: Hsin-Hsi
full_name: Chen, Hsin-Hsi
last_name: Chen
- first_name: Lucia
full_name: Donatelli, Lucia
last_name: Donatelli
- first_name: Heng
full_name: Ji, Heng
last_name: Ji
- first_name: Sadao
full_name: Kurohashi, Sadao
last_name: Kurohashi
- first_name: Patrizia
full_name: Paggio, Patrizia
last_name: Paggio
- first_name: Nianwen
full_name: Xue, Nianwen
last_name: Xue
- first_name: Seokhwan
full_name: Kim, Seokhwan
last_name: Kim
- first_name: Younggyun
full_name: Hahm, Younggyun
last_name: Hahm
- first_name: Zhong
full_name: He, Zhong
last_name: He
- first_name: Tony Kyungil
full_name: Lee, Tony Kyungil
last_name: Lee
- first_name: Enrico
full_name: Santus, Enrico
last_name: Santus
- first_name: Francis
full_name: Bond, Francis
last_name: Bond
- first_name: Seung-Hoon
full_name: Na, Seung-Hoon
last_name: Na
language:
- iso: eng
page: 344–354
place: Gyeongju, Republic of Korea
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: Proceedings of the 29th International Conference on Computational Linguistics
publisher: International Committee on Computational Linguistics
status: public
title: '“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue
Corpus for Learning to Construct Explanations'
type: conference
user_id: '3900'
year: '2022'
...
---
_id: '34067'
author:
- first_name: Meghdut
full_name: Sengupta, Meghdut
id: '99459'
last_name: Sengupta
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Sengupta M, Alshomary M, Wachsmuth H. Back to the Roots: Predicting the Source
Domain of Metaphors using Contrastive Learning. In: Proceedings of the 2022
Workshop on Figurative Language Processing. ; 2022.'
apa: 'Sengupta, M., Alshomary, M., & Wachsmuth, H. (2022). Back to the Roots:
Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings
of the 2022 Workshop on Figurative Language Processing.'
bibtex: '@inproceedings{Sengupta_Alshomary_Wachsmuth_2022, title={Back to the Roots:
Predicting the Source Domain of Metaphors using Contrastive Learning}, booktitle={Proceedings
of the 2022 Workshop on Figurative Language Processing}, author={Sengupta, Meghdut
and Alshomary, Milad and Wachsmuth, Henning}, year={2022} }'
chicago: 'Sengupta, Meghdut, Milad Alshomary, and Henning Wachsmuth. “Back to the
Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.”
In Proceedings of the 2022 Workshop on Figurative Language Processing,
2022.'
ieee: 'M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting
the Source Domain of Metaphors using Contrastive Learning,” 2022.'
mla: 'Sengupta, Meghdut, et al. “Back to the Roots: Predicting the Source Domain
of Metaphors Using Contrastive Learning.” Proceedings of the 2022 Workshop
on Figurative Language Processing, 2022.'
short: 'M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop
on Figurative Language Processing, 2022.'
date_created: 2022-11-14T08:49:07Z
date_updated: 2024-07-26T13:08:46Z
department:
- _id: '600'
- _id: '660'
language:
- iso: eng
project:
- _id: '127'
name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens'
publication: Proceedings of the 2022 Workshop on Figurative Language Processing
status: public
title: 'Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive
Learning'
type: conference
user_id: '3900'
year: '2022'
...
---
_id: '29000'
abstract:
- lang: eng
text: "This thesis aims to provide a bidirectional chatbot solution for the requirement
engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide
the composition of software service On-the-Fly (OTF). The sub-project (B1) of
the SFB 901 project deals with the parameters of service configuration. OTF Computing
aims to eradicate the dependency on the requirement engineers for the software
development process. However, there is no existing bidirectional chatbot solution
that analyses user software requirements and provides viable suggestions to the
user regarding their service. Previously, CORDULA chatbot was developed to analyze
the software requirements but cannot keep the conversation’s context. The Rasa
framework is integrated with the knowledge base to solve the issue, the knowledge
base provides domain-specific knowledge to the chatbot. The software description
is passed through the natural language understanding process to give consciousness
to the chatbot. This process involves various machine learning models, including
app family classification, to correctly identify the domain for user OTF service.
The statistical models like naïve Bayes, kNN and SVM are compared with transformer
models for this classification task. Furthermore, the entities (functional requirements)
are also separated from the user description.\r\nThe chatbot provides the suggestion
of requirements from the preliminary service template with the support of the
knowledge base. Furthermore, the generated response is compared with the state-of-the-art
DialoGPT transformer model and ChatterBot conversational library. These models
are trained over the software development related conversational dataset. All
the responses are ranked using the DialoRPT model, and the BLEU score to evaluates
the models’ responses. Moreover, the chatbot mod- els are tested with human participants,
they used and scored the chatbot responses based on effectiveness, efficiency
and satisfaction. The overall response accuracy is also measured by averaging
the user approval over the generated responses."
author:
- first_name: Mobeen
full_name: Ahmed, Mobeen
last_name: Ahmed
citation:
ama: Ahmed M. Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing.; 2022.
apa: Ahmed, M. (2022). Knowledge Base Enhanced & User-centric Dialogue Design
for OTF Computing.
bibtex: '@book{Ahmed_2022, title={Knowledge Base Enhanced & User-centric Dialogue
Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }'
chicago: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing, 2022.
ieee: M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for
OTF Computing. 2022.
mla: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design
for OTF Computing. 2022.
short: M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for
OTF Computing, 2022.
date_created: 2021-12-16T15:13:07Z
date_updated: 2023-05-02T13:25:45Z
ddc:
- '004'
department:
- _id: '600'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2023-05-02T13:25:27Z
date_updated: 2023-05-02T13:25:27Z
file_id: '44325'
file_name: Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf
file_size: 3092211
relation: main_file
success: 1
file_date_updated: 2023-05-02T13:25:27Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication_status: published
status: public
supervisor:
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
title: Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing
type: mastersthesis
user_id: '58701'
year: '2022'
...
---
_id: '45790'
author:
- first_name: Juela
full_name: Palushi, Juela
last_name: Palushi
citation:
ama: Palushi J. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks.; 2022.
apa: Palushi, J. (2022). Domain-aware Text Professionalization using Sequence-to-Sequence
Neural Networks.
bibtex: '@book{Palushi_2022, title={Domain-aware Text Professionalization using
Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }'
chicago: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks, 2022.
ieee: J. Palushi, Domain-aware Text Professionalization using Sequence-to-Sequence
Neural Networks. 2022.
mla: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks. 2022.
short: J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence
Neural Networks, 2022.
date_created: 2023-06-27T12:57:57Z
date_updated: 2023-07-05T07:31:17Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
status: public
supervisor:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
title: Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks
type: bachelorsthesis
user_id: '477'
year: '2022'
...
---
_id: '45789'
author:
- first_name: Vinaykumar
full_name: Budanurmath, Vinaykumar
last_name: Budanurmath
citation:
ama: Budanurmath V. Propaganda Technique Detection Using Connotation Frames.;
2022.
apa: Budanurmath, V. (2022). Propaganda Technique Detection Using Connotation
Frames.
bibtex: '@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation
Frames}, author={Budanurmath, Vinaykumar}, year={2022} }'
chicago: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation
Frames, 2022.
ieee: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames.
2022.
mla: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation
Frames. 2022.
short: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames,
2022.
date_created: 2023-06-27T12:56:04Z
date_updated: 2023-07-05T07:33:45Z
department:
- _id: '600'
language:
- iso: eng
project:
- _id: '9'
grant_number: '160364472'
name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject
B1)'
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
status: public
supervisor:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
title: Propaganda Technique Detection Using Connotation Frames
type: mastersthesis
user_id: '477'
year: '2022'
...
---
_id: '32247'
author:
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Jonas
full_name: Rieskamp, Jonas
id: '77643'
last_name: Rieskamp
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Alshomary M, Rieskamp J, Wachsmuth H. Generating Contrastive Snippets for
Argument Search. In: Proceedings of the 9th International Conference on Computational
Models of Argument. ; 2022:21-31. doi:http://dx.doi.org/10.3233/FAIA220138'
apa: Alshomary, M., Rieskamp, J., & Wachsmuth, H. (2022). Generating Contrastive
Snippets for Argument Search. Proceedings of the 9th International Conference
on Computational Models of Argument, 21–31. http://dx.doi.org/10.3233/FAIA220138
bibtex: '@inproceedings{Alshomary_Rieskamp_Wachsmuth_2022, title={Generating Contrastive
Snippets for Argument Search}, DOI={http://dx.doi.org/10.3233/FAIA220138},
booktitle={Proceedings of the 9th International Conference on Computational Models
of Argument}, author={Alshomary, Milad and Rieskamp, Jonas and Wachsmuth, Henning},
year={2022}, pages={21–31} }'
chicago: Alshomary, Milad, Jonas Rieskamp, and Henning Wachsmuth. “Generating Contrastive
Snippets for Argument Search.” In Proceedings of the 9th International Conference
on Computational Models of Argument, 21–31, 2022. http://dx.doi.org/10.3233/FAIA220138.
ieee: 'M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets
for Argument Search,” in Proceedings of the 9th International Conference on
Computational Models of Argument, 2022, pp. 21–31, doi: http://dx.doi.org/10.3233/FAIA220138.'
mla: Alshomary, Milad, et al. “Generating Contrastive Snippets for Argument Search.”
Proceedings of the 9th International Conference on Computational Models of
Argument, 2022, pp. 21–31, doi:http://dx.doi.org/10.3233/FAIA220138.
short: 'M. Alshomary, J. Rieskamp, H. Wachsmuth, in: Proceedings of the 9th International
Conference on Computational Models of Argument, 2022, pp. 21–31.'
date_created: 2022-06-28T09:03:30Z
date_updated: 2025-02-20T08:22:16Z
department:
- _id: '600'
- _id: '660'
doi: http://dx.doi.org/10.3233/FAIA220138
language:
- iso: eng
page: 21 - 31
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: Proceedings of the 9th International Conference on Computational Models
of Argument
status: public
title: Generating Contrastive Snippets for Argument Search
type: conference
user_id: '3900'
year: '2022'
...
---
_id: '30840'
author:
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Roxanne
full_name: El Baff, Roxanne
last_name: El Baff
- first_name: Timon
full_name: Gurcke, Timon
id: '52174'
last_name: Gurcke
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Alshomary M, El Baff R, Gurcke T, Wachsmuth H. The Moral Debater: A Study
on the Computational Generation of Morally Framed Arguments. In: Proceedings
of the 60th Annual Meeting of the Association for Computational Linguistics.
; 2022:8782-8797.'
apa: 'Alshomary, M., El Baff, R., Gurcke, T., & Wachsmuth, H. (2022). The Moral
Debater: A Study on the Computational Generation of Morally Framed Arguments.
Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics, 8782–8797.'
bibtex: '@inproceedings{Alshomary_El Baff_Gurcke_Wachsmuth_2022, title={The Moral
Debater: A Study on the Computational Generation of Morally Framed Arguments},
booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics}, author={Alshomary, Milad and El Baff, Roxanne and Gurcke, Timon
and Wachsmuth, Henning}, year={2022}, pages={8782–8797} }'
chicago: 'Alshomary, Milad, Roxanne El Baff, Timon Gurcke, and Henning Wachsmuth.
“The Moral Debater: A Study on the Computational Generation of Morally Framed
Arguments.” In Proceedings of the 60th Annual Meeting of the Association for
Computational Linguistics, 8782–97, 2022.'
ieee: 'M. Alshomary, R. El Baff, T. Gurcke, and H. Wachsmuth, “The Moral Debater:
A Study on the Computational Generation of Morally Framed Arguments,” in Proceedings
of the 60th Annual Meeting of the Association for Computational Linguistics,
2022, pp. 8782–8797.'
mla: 'Alshomary, Milad, et al. “The Moral Debater: A Study on the Computational
Generation of Morally Framed Arguments.” Proceedings of the 60th Annual Meeting
of the Association for Computational Linguistics, 2022, pp. 8782–97.'
short: 'M. Alshomary, R. El Baff, T. Gurcke, H. Wachsmuth, in: Proceedings of the
60th Annual Meeting of the Association for Computational Linguistics, 2022, pp.
8782–8797.'
date_created: 2022-04-06T14:05:45Z
date_updated: 2025-02-20T08:22:46Z
department:
- _id: '600'
- _id: '660'
language:
- iso: eng
page: 8782 - 8797
project:
- _id: '118'
name: 'TRR 318 - INF: TRR 318 - Project Area INF'
publication: Proceedings of the 60th Annual Meeting of the Association for Computational
Linguistics
status: public
title: 'The Moral Debater: A Study on the Computational Generation of Morally Framed
Arguments'
type: conference
user_id: '3900'
year: '2022'
...
---
_id: '20115'
author:
- first_name: Gabriella
full_name: Skitalinskaya, Gabriella
last_name: Skitalinskaya
- first_name: Jonas
full_name: Klaff, Jonas
last_name: Klaff
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Skitalinskaya G, Klaff J, Wachsmuth H. Learning From Revisions: Quality Assessment
of Claims in Argumentation at Scale. In: Proceedings of the 16th Conference
of the European Chapter of the Association for Computational Linguistics.
; 2021:1718-1729.'
apa: 'Skitalinskaya, G., Klaff, J., & Wachsmuth, H. (2021). Learning From Revisions:
Quality Assessment of Claims in Argumentation at Scale. In Proceedings of the
16th Conference of the European Chapter of the Association for Computational Linguistics
(pp. 1718–1729).'
bibtex: '@inproceedings{Skitalinskaya_Klaff_Wachsmuth_2021, title={Learning From
Revisions: Quality Assessment of Claims in Argumentation at Scale}, booktitle={Proceedings
of the 16th Conference of the European Chapter of the Association for Computational
Linguistics}, author={Skitalinskaya, Gabriella and Klaff, Jonas and Wachsmuth,
Henning}, year={2021}, pages={1718–1729} }'
chicago: 'Skitalinskaya, Gabriella, Jonas Klaff, and Henning Wachsmuth. “Learning
From Revisions: Quality Assessment of Claims in Argumentation at Scale.” In Proceedings
of the 16th Conference of the European Chapter of the Association for Computational
Linguistics, 1718–29, 2021.'
ieee: 'G. Skitalinskaya, J. Klaff, and H. Wachsmuth, “Learning From Revisions: Quality
Assessment of Claims in Argumentation at Scale,” in Proceedings of the 16th
Conference of the European Chapter of the Association for Computational Linguistics,
2021, pp. 1718–1729.'
mla: 'Skitalinskaya, Gabriella, et al. “Learning From Revisions: Quality Assessment
of Claims in Argumentation at Scale.” Proceedings of the 16th Conference of
the European Chapter of the Association for Computational Linguistics, 2021,
pp. 1718–29.'
short: 'G. Skitalinskaya, J. Klaff, H. Wachsmuth, in: Proceedings of the 16th Conference
of the European Chapter of the Association for Computational Linguistics, 2021,
pp. 1718–1729.'
date_created: 2020-10-16T12:39:27Z
date_updated: 2022-01-06T06:54:19Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/2021.eacl-main.147/
page: 1718-1729
publication: Proceedings of the 16th Conference of the European Chapter of the Association
for Computational Linguistics
status: public
title: 'Learning From Revisions: Quality Assessment of Claims in Argumentation at
Scale'
type: conference
user_id: '82920'
year: '2021'
...