---
_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. <i>Proceedings of the 29th International
    Conference on Computational Linguistics</i>. International Committee on Computational
    Linguistics; 2022:344–354.'
  apa: 'Wachsmuth, H., &#38; 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, &#38; S.-H. Na (Eds.), <i>Proceedings
    of the 29th International Conference on Computational Linguistics</i> (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 <i>Proceedings of the 29th International Conference on Computational Linguistics</i>,
    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 <i>Proceedings of the 29th International Conference on Computational Linguistics</i>,
    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.”
    <i>Proceedings of the 29th International Conference on Computational Linguistics</i>,
    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: <i>Proceedings of the 2022
    Workshop on Figurative Language Processing</i>. ; 2022.'
  apa: 'Sengupta, M., Alshomary, M., &#38; Wachsmuth, H. (2022). Back to the Roots:
    Predicting the Source Domain of Metaphors using Contrastive Learning. <i>Proceedings
    of the 2022 Workshop on Figurative Language Processing</i>.'
  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 <i>Proceedings of the 2022 Workshop on Figurative Language Processing</i>,
    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.” <i>Proceedings of the 2022 Workshop
    on Figurative Language Processing</i>, 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. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design for
    OTF Computing</i>.; 2022.
  apa: Ahmed, M. (2022). <i>Knowledge Base Enhanced &#38; User-centric Dialogue Design
    for OTF Computing</i>.
  bibtex: '@book{Ahmed_2022, title={Knowledge Base Enhanced &#38; User-centric Dialogue
    Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }'
  chicago: Ahmed, Mobeen. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design
    for OTF Computing</i>, 2022.
  ieee: M. Ahmed, <i>Knowledge Base Enhanced &#38; User-centric Dialogue Design for
    OTF Computing</i>. 2022.
  mla: Ahmed, Mobeen. <i>Knowledge Base Enhanced &#38; User-Centric Dialogue Design
    for OTF Computing</i>. 2022.
  short: M. Ahmed, Knowledge Base Enhanced &#38; 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. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence
    Neural Networks</i>.; 2022.
  apa: Palushi, J. (2022). <i>Domain-aware Text Professionalization using Sequence-to-Sequence
    Neural Networks</i>.
  bibtex: '@book{Palushi_2022, title={Domain-aware Text Professionalization using
    Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }'
  chicago: Palushi, Juela. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence
    Neural Networks</i>, 2022.
  ieee: J. Palushi, <i>Domain-aware Text Professionalization using Sequence-to-Sequence
    Neural Networks</i>. 2022.
  mla: Palushi, Juela. <i>Domain-Aware Text Professionalization Using Sequence-to-Sequence
    Neural Networks</i>. 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. <i>Propaganda Technique Detection Using Connotation Frames</i>.;
    2022.
  apa: Budanurmath, V. (2022). <i>Propaganda Technique Detection Using Connotation
    Frames</i>.
  bibtex: '@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation
    Frames}, author={Budanurmath, Vinaykumar}, year={2022} }'
  chicago: Budanurmath, Vinaykumar. <i>Propaganda Technique Detection Using Connotation
    Frames</i>, 2022.
  ieee: V. Budanurmath, <i>Propaganda Technique Detection Using Connotation Frames</i>.
    2022.
  mla: Budanurmath, Vinaykumar. <i>Propaganda Technique Detection Using Connotation
    Frames</i>. 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: <i>Proceedings of the 9th International Conference on Computational
    Models of Argument</i>. ; 2022:21-31. doi:<a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>'
  apa: Alshomary, M., Rieskamp, J., &#38; Wachsmuth, H. (2022). Generating Contrastive
    Snippets for Argument Search. <i>Proceedings of the 9th International Conference
    on Computational Models of Argument</i>, 21–31. <a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>
  bibtex: '@inproceedings{Alshomary_Rieskamp_Wachsmuth_2022, title={Generating Contrastive
    Snippets for Argument Search}, DOI={<a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>},
    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 <i>Proceedings of the 9th International Conference
    on Computational Models of Argument</i>, 21–31, 2022. <a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>.
  ieee: 'M. Alshomary, J. Rieskamp, and H. Wachsmuth, “Generating Contrastive Snippets
    for Argument Search,” in <i>Proceedings of the 9th International Conference on
    Computational Models of Argument</i>, 2022, pp. 21–31, doi: <a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>.'
  mla: Alshomary, Milad, et al. “Generating Contrastive Snippets for Argument Search.”
    <i>Proceedings of the 9th International Conference on Computational Models of
    Argument</i>, 2022, pp. 21–31, doi:<a href="http://dx.doi.org/10.3233/FAIA220138">http://dx.doi.org/10.3233/FAIA220138</a>.
  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: <i>Proceedings
    of the 60th Annual Meeting of the Association for Computational Linguistics</i>.
    ; 2022:8782-8797.'
  apa: 'Alshomary, M., El Baff, R., Gurcke, T., &#38; Wachsmuth, H. (2022). The Moral
    Debater: A Study on the Computational Generation of Morally Framed Arguments.
    <i>Proceedings of the 60th Annual Meeting of the Association for Computational
    Linguistics</i>, 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 <i>Proceedings of the 60th Annual Meeting of the Association for
    Computational Linguistics</i>, 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 <i>Proceedings
    of the 60th Annual Meeting of the Association for Computational Linguistics</i>,
    2022, pp. 8782–8797.'
  mla: 'Alshomary, Milad, et al. “The Moral Debater: A Study on the Computational
    Generation of Morally Framed Arguments.” <i>Proceedings of the 60th Annual Meeting
    of the Association for Computational Linguistics</i>, 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: <i>Proceedings of the 16th Conference
    of the European Chapter of the Association for Computational Linguistics</i>.
    ; 2021:1718-1729.'
  apa: 'Skitalinskaya, G., Klaff, J., &#38; Wachsmuth, H. (2021). Learning From Revisions:
    Quality Assessment of Claims in Argumentation at Scale. In <i>Proceedings of the
    16th Conference of the European Chapter of the Association for Computational Linguistics</i>
    (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 <i>Proceedings
    of the 16th Conference of the European Chapter of the Association for Computational
    Linguistics</i>, 1718–29, 2021.'
  ieee: 'G. Skitalinskaya, J. Klaff, and H. Wachsmuth, “Learning From Revisions: Quality
    Assessment of Claims in Argumentation at Scale,” in <i>Proceedings of the 16th
    Conference of the European Chapter of the Association for Computational Linguistics</i>,
    2021, pp. 1718–1729.'
  mla: 'Skitalinskaya, Gabriella, et al. “Learning From Revisions: Quality Assessment
    of Claims in Argumentation at Scale.” <i>Proceedings of the 16th Conference of
    the European Chapter of the Association for Computational Linguistics</i>, 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'
...
---
_id: '3774'
author:
- first_name: Alexander
  full_name: Bondarenko, Alexander
  last_name: Bondarenko
- first_name: Lukas
  full_name: Gienapp, Lukas
  last_name: Gienapp
- first_name: Maik
  full_name: Fröbe, Maik
  last_name: Fröbe
- first_name: Meriem
  full_name: Beloucif, Meriem
  last_name: Beloucif
- first_name: Yamen
  full_name: Ajjour, Yamen
  last_name: Ajjour
- 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
  id: '3900'
  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, Gienapp L, Fröbe M, et al. Overview of Touché 2021: Argument
    Retrieval. In: <i>Proceedings of the 43rd Annual European Conference on Information
    Retrieval Research</i>. ; 2021:384-395.'
  apa: 'Bondarenko, A., Gienapp, L., Fröbe, M., Beloucif, M., Ajjour, Y., Panchenko,
    A., … Hagen, M. (2021). Overview of Touché 2021: Argument Retrieval. In <i>Proceedings
    of the 43rd annual European Conference on Information Retrieval Research</i> (pp.
    384–395).'
  bibtex: '@inproceedings{Bondarenko_Gienapp_Fröbe_Beloucif_Ajjour_Panchenko_Biemann_Stein_Wachsmuth_Potthast_et
    al._2021, title={Overview of Touché 2021: Argument Retrieval}, booktitle={Proceedings
    of the 43rd annual European Conference on Information Retrieval Research}, author={Bondarenko,
    Alexander and Gienapp, Lukas and Fröbe, Maik and Beloucif, Meriem and Ajjour,
    Yamen and Panchenko, Alexander and Biemann, Chris and Stein, Benno and Wachsmuth,
    Henning and Potthast, Martin and et al.}, year={2021}, pages={384–395} }'
  chicago: 'Bondarenko, Alexander, Lukas Gienapp, Maik Fröbe, Meriem Beloucif, Yamen
    Ajjour, Alexander Panchenko, Chris Biemann, et al. “Overview of Touché 2021: Argument
    Retrieval.” In <i>Proceedings of the 43rd Annual European Conference on Information
    Retrieval Research</i>, 384–95, 2021.'
  ieee: 'A. Bondarenko <i>et al.</i>, “Overview of Touché 2021: Argument Retrieval,”
    in <i>Proceedings of the 43rd annual European Conference on Information Retrieval
    Research</i>, 2021, pp. 384–395.'
  mla: 'Bondarenko, Alexander, et al. “Overview of Touché 2021: Argument Retrieval.”
    <i>Proceedings of the 43rd Annual European Conference on Information Retrieval
    Research</i>, 2021, pp. 384–95.'
  short: 'A. Bondarenko, L. Gienapp, M. Fröbe, M. Beloucif, Y. Ajjour, A. Panchenko,
    C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Proceedings of
    the 43rd Annual European Conference on Information Retrieval Research, 2021, pp.
    384–395.'
date_created: 2018-08-02T11:40:53Z
date_updated: 2022-01-06T06:59:35Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://webis.de/downloads/publications/papers/bondarenko_2021.pdf
page: 384-395
publication: Proceedings of the 43rd annual European Conference on Information Retrieval
  Research
status: public
title: 'Overview of Touché 2021: Argument Retrieval'
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '23708'
author:
- first_name: Zahra
  full_name: Nouri, Zahra
  id: '35802'
  last_name: Nouri
- first_name: Ujwal
  full_name: Gadiraju, Ujwal
  last_name: Gadiraju
- first_name: Gregor
  full_name: Engels, Gregor
  id: '107'
  last_name: Engels
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Nouri Z, Gadiraju U, Engels G, Wachsmuth H. What Is Unclear? Computational
    Assessment of Task Clarity in Crowdsourcing. In: <i>Proceedings of the 32nd ACM
    Conference on Hypertext and Social Media</i>. ; 2021:165-175.'
  apa: Nouri, Z., Gadiraju, U., Engels, G., &#38; Wachsmuth, H. (2021). What Is Unclear?
    Computational Assessment of Task Clarity in Crowdsourcing. <i>Proceedings of the
    32nd ACM Conference on Hypertext and Social Media</i>, 165–175.
  bibtex: '@inproceedings{Nouri_Gadiraju_Engels_Wachsmuth_2021, title={What Is Unclear?
    Computational Assessment of Task Clarity in Crowdsourcing}, booktitle={Proceedings
    of the 32nd ACM Conference on Hypertext and Social Media}, author={Nouri, Zahra
    and Gadiraju, Ujwal and Engels, Gregor and Wachsmuth, Henning}, year={2021}, pages={165–175}
    }'
  chicago: Nouri, Zahra, Ujwal Gadiraju, Gregor Engels, and Henning Wachsmuth. “What
    Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing.” In <i>Proceedings
    of the 32nd ACM Conference on Hypertext and Social Media</i>, 165–75, 2021.
  ieee: Z. Nouri, U. Gadiraju, G. Engels, and H. Wachsmuth, “What Is Unclear? Computational
    Assessment of Task Clarity in Crowdsourcing,” in <i>Proceedings of the 32nd ACM
    Conference on Hypertext and Social Media</i>, 2021, pp. 165–175.
  mla: Nouri, Zahra, et al. “What Is Unclear? Computational Assessment of Task Clarity
    in Crowdsourcing.” <i>Proceedings of the 32nd ACM Conference on Hypertext and
    Social Media</i>, 2021, pp. 165–75.
  short: 'Z. Nouri, U. Gadiraju, G. Engels, H. Wachsmuth, in: Proceedings of the 32nd
    ACM Conference on Hypertext and Social Media, 2021, pp. 165–175.'
date_created: 2021-09-02T20:05:52Z
date_updated: 2022-01-06T06:55:58Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://dl.acm.org/doi/pdf/10.1145/3465336.3475109
oa: '1'
page: 165-175
publication: Proceedings of the 32nd ACM Conference on Hypertext and Social Media
status: public
title: What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22156'
abstract:
- lang: eng
  text: Word embedding models reflect bias towards genders, ethnicities, and other
    social groups present in the underlying training data. Metrics such as ECT, RNSB,
    and WEAT quantify bias in these models based on predefined word lists representing
    social groups and bias-conveying concepts. How suitable these lists actually are
    to reveal bias - let alone the bias metrics in general - remains unclear, though.
    In this paper, we study how to assess the quality of bias metrics for word embedding
    models. In particular, we present a generic method, Bias Silhouette Analysis (BSA),
    that quantifies the accuracy and robustness of such a metric and of the word lists
    used. Given a biased and an unbiased reference embedding model, BSA applies the
    metric systematically for several subsets of the lists to the models. The variance
    and rate of convergence of the bias values of each model then entail the robustness
    of the word lists, whereas the distance between the models' values gives indications
    of the general accuracy of the metric with the word lists. We demonstrate the
    behavior of BSA on two standard embedding models for the three mentioned metrics
    with several word lists from existing research.
author:
- first_name: Maximilian
  full_name: Spliethöver, Maximilian
  id: '84035'
  last_name: Spliethöver
  orcid: 0000-0003-4364-1409
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Spliethöver M, Wachsmuth H. Bias Silhouette Analysis: Towards Assessing the
    Quality of Bias Metrics for Word Embedding Models. In: <i>Proceedings of the Thirtieth
    International Joint Conference on Artificial Intelligence, IJCAI-21</i>. ; 2021:552-559.
    doi:<a href="https://doi.org/10.24963/ijcai.2021/77">10.24963/ijcai.2021/77</a>'
  apa: 'Spliethöver, M., &#38; Wachsmuth, H. (2021). Bias Silhouette Analysis: Towards
    Assessing the Quality of Bias Metrics for Word Embedding Models. <i>Proceedings
    of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21</i>,
    552–559. <a href="https://doi.org/10.24963/ijcai.2021/77">https://doi.org/10.24963/ijcai.2021/77</a>'
  bibtex: '@inproceedings{Spliethöver_Wachsmuth_2021, title={Bias Silhouette Analysis:
    Towards Assessing the Quality of Bias Metrics for Word Embedding Models}, DOI={<a
    href="https://doi.org/10.24963/ijcai.2021/77">10.24963/ijcai.2021/77</a>}, booktitle={Proceedings
    of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21},
    author={Spliethöver, Maximilian and Wachsmuth, Henning}, year={2021}, pages={552–559}
    }'
  chicago: 'Spliethöver, Maximilian, and Henning Wachsmuth. “Bias Silhouette Analysis:
    Towards Assessing the Quality of Bias Metrics for Word Embedding Models.” In <i>Proceedings
    of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21</i>,
    552–59, 2021. <a href="https://doi.org/10.24963/ijcai.2021/77">https://doi.org/10.24963/ijcai.2021/77</a>.'
  ieee: 'M. Spliethöver and H. Wachsmuth, “Bias Silhouette Analysis: Towards Assessing
    the Quality of Bias Metrics for Word Embedding Models,” in <i>Proceedings of the
    Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21</i>,
    Online, 2021, pp. 552–559, doi: <a href="https://doi.org/10.24963/ijcai.2021/77">10.24963/ijcai.2021/77</a>.'
  mla: 'Spliethöver, Maximilian, and Henning Wachsmuth. “Bias Silhouette Analysis:
    Towards Assessing the Quality of Bias Metrics for Word Embedding Models.” <i>Proceedings
    of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21</i>,
    2021, pp. 552–59, doi:<a href="https://doi.org/10.24963/ijcai.2021/77">10.24963/ijcai.2021/77</a>.'
  short: 'M. Spliethöver, H. Wachsmuth, in: Proceedings of the Thirtieth International
    Joint Conference on Artificial Intelligence, IJCAI-21, 2021, pp. 552–559.'
conference:
  end_date: 2021-08-26
  location: Online
  name: 30th International Joint Conference on Artificial Intelligence (IJCAI-21)
  start_date: 2021-08-19
date_created: 2021-05-11T23:13:26Z
date_updated: 2022-01-06T06:55:28Z
department:
- _id: '600'
doi: 10.24963/ijcai.2021/77
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.ijcai.org/proceedings/2021/77
oa: '1'
page: 552-559
publication: Proceedings of the Thirtieth International Joint Conference on Artificial
  Intelligence, IJCAI-21
quality_controlled: '1'
status: public
title: 'Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for
  Word Embedding Models'
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22158'
author:
- first_name: Shahbaz
  full_name: Syed, Shahbaz
  last_name: Syed
- first_name: Khalid
  full_name: Al-Khatib, Khalid
  last_name: Al-Khatib
- first_name: Milad
  full_name: Alshomary, Milad
  id: '73059'
  last_name: Alshomary
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
- first_name: Martin
  full_name: Potthast, Martin
  last_name: Potthast
citation:
  ama: 'Syed S, Al-Khatib K, Alshomary M, Wachsmuth H, Potthast M. Generating Informative
    Conclusions for Argumentative Texts. In: <i>Proceedings of the Joint Conference
    of the 59th Annual Meeting of the Association for Computational Linguistics and
    the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP
    2021): Findings</i>. ; 2021:3482-3493.'
  apa: 'Syed, S., Al-Khatib, K., Alshomary, M., Wachsmuth, H., &#38; Potthast, M.
    (2021). Generating Informative Conclusions for Argumentative Texts. <i>Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021): Findings</i>, 3482–3493.'
  bibtex: '@inproceedings{Syed_Al-Khatib_Alshomary_Wachsmuth_Potthast_2021, title={Generating
    Informative Conclusions for Argumentative Texts}, booktitle={Proceedings of the
    Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021): Findings}, author={Syed, Shahbaz and Al-Khatib, Khalid and
    Alshomary, Milad and Wachsmuth, Henning and Potthast, Martin}, year={2021}, pages={3482–3493}
    }'
  chicago: 'Syed, Shahbaz, Khalid Al-Khatib, Milad Alshomary, Henning Wachsmuth, and
    Martin Potthast. “Generating Informative Conclusions for Argumentative Texts.”
    In <i>Proceedings of the Joint Conference of the 59th Annual Meeting of the Association
    for Computational Linguistics and the 11th International Joint Conference on Natural
    Language Processing (ACL-IJCNLP 2021): Findings</i>, 3482–93, 2021.'
  ieee: 'S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, and M. Potthast, “Generating
    Informative Conclusions for Argumentative Texts,” in <i>Proceedings of the Joint
    Conference of the 59th Annual Meeting of the Association for Computational Linguistics
    and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP
    2021): Findings</i>, 2021, pp. 3482–3493.'
  mla: 'Syed, Shahbaz, et al. “Generating Informative Conclusions for Argumentative
    Texts.” <i>Proceedings of the Joint Conference of the 59th Annual Meeting of the
    Association for Computational Linguistics and the 11th International Joint Conference
    on Natural Language Processing (ACL-IJCNLP 2021): Findings</i>, 2021, pp. 3482–93.'
  short: 'S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, M. Potthast, in: Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021): Findings, 2021, pp. 3482–3493.'
date_created: 2021-05-11T23:18:14Z
date_updated: 2022-01-06T06:55:28Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://aclanthology.org/2021.findings-acl.306.pdf
oa: '1'
page: 3482-3493
publication: 'Proceedings of the Joint Conference of the 59th Annual Meeting of the
  Association for Computational Linguistics and the 11th International Joint Conference
  on Natural Language Processing (ACL-IJCNLP 2021): Findings'
status: public
title: Generating Informative Conclusions for Argumentative Texts
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22159'
author:
- first_name: Joe
  full_name: Barrow, Joe
  last_name: Barrow
- first_name: Rajiv
  full_name: Jain, Rajiv
  last_name: Jain
- first_name: Nedim
  full_name: Lipka, Nedim
  last_name: Lipka
- first_name: Franck
  full_name: Dernoncourt, Franck
  last_name: Dernoncourt
- first_name: Vlad
  full_name: Morariu, Vlad
  last_name: Morariu
- first_name: Varun
  full_name: Manjunatha, Varun
  last_name: Manjunatha
- first_name: Douglas
  full_name: Oard, Douglas
  last_name: Oard
- first_name: Philip
  full_name: Resnik, Philip
  last_name: Resnik
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Barrow J, Jain R, Lipka N, et al. Syntopical Graphs for Computational Argumentation
    Tasks. In: <i>Proceedings of the Joint Conference of the 59th Annual Meeting of
    the Association for Computational Linguistics and the 11th International Joint
    Conference on Natural Language Processing (ACL-IJCNLP 2021)</i>. ; 2021:1583-1595.'
  apa: Barrow, J., Jain, R., Lipka, N., Dernoncourt, F., Morariu, V., Manjunatha,
    V., Oard, D., Resnik, P., &#38; Wachsmuth, H. (2021). Syntopical Graphs for Computational
    Argumentation Tasks. <i>Proceedings of the Joint Conference of the 59th Annual
    Meeting of the Association for Computational Linguistics and the 11th International
    Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)</i>, 1583–1595.
  bibtex: '@inproceedings{Barrow_Jain_Lipka_Dernoncourt_Morariu_Manjunatha_Oard_Resnik_Wachsmuth_2021,
    title={Syntopical Graphs for Computational Argumentation Tasks}, booktitle={Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021)}, author={Barrow, Joe and Jain, Rajiv and Lipka, Nedim and Dernoncourt,
    Franck and Morariu, Vlad and Manjunatha, Varun and Oard, Douglas and Resnik, Philip
    and Wachsmuth, Henning}, year={2021}, pages={1583–1595} }'
  chicago: Barrow, Joe, Rajiv Jain, Nedim Lipka, Franck Dernoncourt, Vlad Morariu,
    Varun Manjunatha, Douglas Oard, Philip Resnik, and Henning Wachsmuth. “Syntopical
    Graphs for Computational Argumentation Tasks.” In <i>Proceedings of the Joint
    Conference of the 59th Annual Meeting of the Association for Computational Linguistics
    and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP
    2021)</i>, 1583–95, 2021.
  ieee: J. Barrow <i>et al.</i>, “Syntopical Graphs for Computational Argumentation
    Tasks,” in <i>Proceedings of the Joint Conference of the 59th Annual Meeting of
    the Association for Computational Linguistics and the 11th International Joint
    Conference on Natural Language Processing (ACL-IJCNLP 2021)</i>, 2021, pp. 1583–1595.
  mla: Barrow, Joe, et al. “Syntopical Graphs for Computational Argumentation Tasks.”
    <i>Proceedings of the Joint Conference of the 59th Annual Meeting of the Association
    for Computational Linguistics and the 11th International Joint Conference on Natural
    Language Processing (ACL-IJCNLP 2021)</i>, 2021, pp. 1583–95.
  short: 'J. Barrow, R. Jain, N. Lipka, F. Dernoncourt, V. Morariu, V. Manjunatha,
    D. Oard, P. Resnik, H. Wachsmuth, in: Proceedings of the Joint Conference of the
    59th Annual Meeting of the Association for Computational Linguistics and the 11th
    International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021),
    2021, pp. 1583–1595.'
date_created: 2021-05-11T23:20:59Z
date_updated: 2022-01-06T06:55:28Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://aclanthology.org/2021.acl-long.126.pdf
oa: '1'
page: 1583-1595
publication: Proceedings of the Joint Conference of the 59th Annual Meeting of the
  Association for Computational Linguistics and the 11th International Joint Conference
  on Natural Language Processing (ACL-IJCNLP 2021)
status: public
title: Syntopical Graphs for Computational Argumentation Tasks
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22160'
author:
- first_name: Khalid
  full_name: Al-Khatib, Khalid
  last_name: Al-Khatib
- first_name: Lukas
  full_name: Trautner, Lukas
  last_name: Trautner
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
- first_name: Yufang
  full_name: Hou, Yufang
  last_name: Hou
- first_name: Benno
  full_name: Stein, Benno
  last_name: Stein
citation:
  ama: 'Al-Khatib K, Trautner L, Wachsmuth H, Hou Y, Stein B. Employing Argumentation
    Knowledge Graphs for Neural Argument Generation. In: <i>Proceedings of the Joint
    Conference of the 59th Annual Meeting of the Association for Computational Linguistics
    and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP
    2021)</i>. ; 2021:4744-4754.'
  apa: Al-Khatib, K., Trautner, L., Wachsmuth, H., Hou, Y., &#38; Stein, B. (2021).
    Employing Argumentation Knowledge Graphs for Neural Argument Generation. <i>Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021)</i>, 4744–4754.
  bibtex: '@inproceedings{Al-Khatib_Trautner_Wachsmuth_Hou_Stein_2021, title={Employing
    Argumentation Knowledge Graphs for Neural Argument Generation}, booktitle={Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021)}, author={Al-Khatib, Khalid and Trautner, Lukas and Wachsmuth,
    Henning and Hou, Yufang and Stein, Benno}, year={2021}, pages={4744–4754} }'
  chicago: Al-Khatib, Khalid, Lukas Trautner, Henning Wachsmuth, Yufang Hou, and Benno
    Stein. “Employing Argumentation Knowledge Graphs for Neural Argument Generation.”
    In <i>Proceedings of the Joint Conference of the 59th Annual Meeting of the Association
    for Computational Linguistics and the 11th International Joint Conference on Natural
    Language Processing (ACL-IJCNLP 2021)</i>, 4744–54, 2021.
  ieee: K. Al-Khatib, L. Trautner, H. Wachsmuth, Y. Hou, and B. Stein, “Employing
    Argumentation Knowledge Graphs for Neural Argument Generation,” in <i>Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021)</i>, 2021, pp. 4744–4754.
  mla: Al-Khatib, Khalid, et al. “Employing Argumentation Knowledge Graphs for Neural
    Argument Generation.” <i>Proceedings of the Joint Conference of the 59th Annual
    Meeting of the Association for Computational Linguistics and the 11th International
    Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)</i>, 2021, pp.
    4744–54.
  short: 'K. Al-Khatib, L. Trautner, H. Wachsmuth, Y. Hou, B. Stein, in: Proceedings
    of the Joint Conference of the 59th Annual Meeting of the Association for Computational
    Linguistics and the 11th International Joint Conference on Natural Language Processing
    (ACL-IJCNLP 2021), 2021, pp. 4744–4754.'
date_created: 2021-05-11T23:22:36Z
date_updated: 2022-01-06T06:55:28Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.acl-long.366.pdf
page: 4744-4754
publication: Proceedings of the Joint Conference of the 59th Annual Meeting of the
  Association for Computational Linguistics and the 11th International Joint Conference
  on Natural Language Processing (ACL-IJCNLP 2021)
status: public
title: Employing Argumentation Knowledge Graphs for Neural Argument Generation
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22448'
author:
- first_name: Johannes
  full_name: Kiesel, Johannes
  last_name: Kiesel
- first_name: Damiano
  full_name: Spina, Damiano
  last_name: Spina
- 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, Spina D, Wachsmuth H, Stein B. The Meant, the Said, and the Understood:
    Conversational Argument Search and Cognitive Biases. In: <i>Proceedings of the
    2021 Conversational User Interfaces Conference</i>. ; 2021:1-5.'
  apa: 'Kiesel, J., Spina, D., Wachsmuth, H., &#38; Stein, B. (2021). The Meant, the
    Said, and the Understood: Conversational Argument Search and Cognitive Biases.
    <i>Proceedings of the 2021 Conversational User Interfaces Conference</i>, 1–5.'
  bibtex: '@inproceedings{Kiesel_Spina_Wachsmuth_Stein_2021, title={The Meant, the
    Said, and the Understood: Conversational Argument Search and Cognitive Biases},
    booktitle={Proceedings of the 2021 Conversational User Interfaces Conference},
    author={Kiesel, Johannes and Spina, Damiano and Wachsmuth, Henning and Stein,
    Benno}, year={2021}, pages={1–5} }'
  chicago: 'Kiesel, Johannes, Damiano Spina, Henning Wachsmuth, and Benno Stein. “The
    Meant, the Said, and the Understood: Conversational Argument Search and Cognitive
    Biases.” In <i>Proceedings of the 2021 Conversational User Interfaces Conference</i>,
    1–5, 2021.'
  ieee: 'J. Kiesel, D. Spina, H. Wachsmuth, and B. Stein, “The Meant, the Said, and
    the Understood: Conversational Argument Search and Cognitive Biases,” in <i>Proceedings
    of the 2021 Conversational User Interfaces Conference</i>, 2021, pp. 1–5.'
  mla: 'Kiesel, Johannes, et al. “The Meant, the Said, and the Understood: Conversational
    Argument Search and Cognitive Biases.” <i>Proceedings of the 2021 Conversational
    User Interfaces Conference</i>, 2021, pp. 1–5.'
  short: 'J. Kiesel, D. Spina, H. Wachsmuth, B. Stein, in: Proceedings of the 2021
    Conversational User Interfaces Conference, 2021, pp. 1–5.'
date_created: 2021-06-15T13:51:36Z
date_updated: 2022-01-06T06:55:33Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://dl.acm.org/doi/fullHtml/10.1145/3469595.3469615
page: 1-5
publication: Proceedings of the 2021 Conversational User Interfaces Conference
status: public
title: 'The Meant, the Said, and the Understood: Conversational Argument Search and
  Cognitive Biases'
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '22449'
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. Toward Audience-aware Argument Generation. <i>Patterns</i>.
    2021;2(6).
  apa: Alshomary, M., &#38; Wachsmuth, H. (2021). Toward Audience-aware Argument Generation.
    <i>Patterns</i>, <i>2</i>(6).
  bibtex: '@article{Alshomary_Wachsmuth_2021, title={Toward Audience-aware Argument
    Generation}, volume={2}, number={6}, journal={Patterns}, author={Alshomary, Milad
    and Wachsmuth, Henning}, year={2021} }'
  chicago: Alshomary, Milad, and Henning Wachsmuth. “Toward Audience-Aware Argument
    Generation.” <i>Patterns</i> 2, no. 6 (2021).
  ieee: M. Alshomary and H. Wachsmuth, “Toward Audience-aware Argument Generation,”
    <i>Patterns</i>, vol. 2, no. 6, 2021.
  mla: Alshomary, Milad, and Henning Wachsmuth. “Toward Audience-Aware Argument Generation.”
    <i>Patterns</i>, vol. 2, no. 6, 2021.
  short: M. Alshomary, H. Wachsmuth, Patterns 2 (2021).
date_created: 2021-06-15T13:53:52Z
date_updated: 2022-01-06T06:55:33Z
intvolume: '         2'
issue: '6'
language:
- iso: eng
main_file_link:
- url: https://www.sciencedirect.com/science/article/pii/S2666389921000799
publication: Patterns
status: public
title: Toward Audience-aware Argument Generation
type: journal_article
user_id: '82920'
volume: 2
year: '2021'
...
---
_id: '25297'
author:
- first_name: Milad
  full_name: Alshomary, Milad
  id: '73059'
  last_name: Alshomary
- first_name: Timon
  full_name: Gurcke, Timon
  id: '52174'
  last_name: Gurcke
- first_name: Shahbaz
  full_name: Syed, Shahbaz
  last_name: Syed
- first_name: Philipp
  full_name: Heinisch, Philipp
  last_name: Heinisch
- first_name: Maximilian
  full_name: Spliethöver, Maximilian
  id: '84035'
  last_name: Spliethöver
  orcid: 0000-0003-4364-1409
- first_name: Philipp
  full_name: Cimiano, Philipp
  last_name: Cimiano
- first_name: Martin
  full_name: Potthast, Martin
  last_name: Potthast
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Alshomary M, Gurcke T, Syed S, et al. Key Point Analysis via Contrastive Learning
    and Extractive Argument Summarization. In: <i>Proceedings of the 8th Workshop
    on Argument Mining</i>. ; 2021:184-189.'
  apa: Alshomary, M., Gurcke, T., Syed, S., Heinisch, P., Spliethöver, M., Cimiano,
    P., Potthast, M., &#38; Wachsmuth, H. (2021). Key Point Analysis via Contrastive
    Learning and Extractive Argument Summarization. <i>Proceedings of the 8th Workshop
    on Argument Mining</i>, 184–189.
  bibtex: '@inproceedings{Alshomary_Gurcke_Syed_Heinisch_Spliethöver_Cimiano_Potthast_Wachsmuth_2021,
    title={Key Point Analysis via Contrastive Learning and Extractive Argument Summarization},
    booktitle={Proceedings of the 8th Workshop on Argument Mining}, author={Alshomary,
    Milad and Gurcke, Timon and Syed, Shahbaz and Heinisch, Philipp and Spliethöver,
    Maximilian and Cimiano, Philipp and Potthast, Martin and Wachsmuth, Henning},
    year={2021}, pages={184–189} }'
  chicago: Alshomary, Milad, Timon Gurcke, Shahbaz Syed, Philipp Heinisch, Maximilian
    Spliethöver, Philipp Cimiano, Martin Potthast, and Henning Wachsmuth. “Key Point
    Analysis via Contrastive Learning and Extractive Argument Summarization.” In <i>Proceedings
    of the 8th Workshop on Argument Mining</i>, 184–89, 2021.
  ieee: M. Alshomary <i>et al.</i>, “Key Point Analysis via Contrastive Learning and
    Extractive Argument Summarization,” in <i>Proceedings of the 8th Workshop on Argument
    Mining</i>, 2021, pp. 184–189.
  mla: Alshomary, Milad, et al. “Key Point Analysis via Contrastive Learning and Extractive
    Argument Summarization.” <i>Proceedings of the 8th Workshop on Argument Mining</i>,
    2021, pp. 184–89.
  short: 'M. Alshomary, T. Gurcke, S. Syed, P. Heinisch, M. Spliethöver, P. Cimiano,
    M. Potthast, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining,
    2021, pp. 184–189.'
date_created: 2021-10-04T12:40:02Z
date_updated: 2022-03-08T12:47:33Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.argmining-1.19.pdf
page: 184 - 189
publication: Proceedings of the 8th Workshop on Argument Mining
status: public
title: Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '25294'
author:
- first_name: Zahra
  full_name: Nouri, Zahra
  id: '35802'
  last_name: Nouri
- first_name: Nikhil
  full_name: Prakash, Nikhil
  last_name: Prakash
- first_name: Ujwal
  full_name: Gadiraju, Ujwal
  last_name: Gadiraju
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Nouri Z, Prakash N, Gadiraju U, Wachsmuth H. iClarify - A Tool to Help Requesters
    Iteratively Improve Task Descriptions in Crowdsourcing. In: <i>Proceedings of
    the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021</i>.
    ; 2021.'
  apa: Nouri, Z., Prakash, N., Gadiraju, U., &#38; Wachsmuth, H. (2021). iClarify
    - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing.
    <i>Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing,
    HCOMP 2021</i>.
  bibtex: '@inproceedings{Nouri_Prakash_Gadiraju_Wachsmuth_2021, title={iClarify -
    A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing},
    booktitle={Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing,
    HCOMP 2021}, author={Nouri, Zahra and Prakash, Nikhil and Gadiraju, Ujwal and
    Wachsmuth, Henning}, year={2021} }'
  chicago: Nouri, Zahra, Nikhil Prakash, Ujwal Gadiraju, and Henning Wachsmuth. “IClarify
    - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing.”
    In <i>Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing,
    HCOMP 2021</i>, 2021.
  ieee: Z. Nouri, N. Prakash, U. Gadiraju, and H. Wachsmuth, “iClarify - A Tool to
    Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing,” 2021.
  mla: Nouri, Zahra, et al. “IClarify - A Tool to Help Requesters Iteratively Improve
    Task Descriptions in Crowdsourcing.” <i>Proceedings of the Ninth AAAI Conference
    on Human Computation and Crowdsourcing, HCOMP 2021</i>, 2021.
  short: 'Z. Nouri, N. Prakash, U. Gadiraju, H. Wachsmuth, in: Proceedings of the
    Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021, 2021.'
date_created: 2021-10-04T12:35:50Z
date_updated: 2022-03-08T12:46:44Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://www.humancomputation.com/assets/wips_demos/HCOMP_2021_paper_111.pdf
publication: Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing,
  HCOMP 2021
status: public
title: iClarify - A Tool to Help Requesters Iteratively Improve Task Descriptions
  in Crowdsourcing
type: conference
user_id: '82920'
year: '2021'
...
---
_id: '25295'
author:
- first_name: Timon
  full_name: Gurcke, Timon
  id: '52174'
  last_name: Gurcke
- 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: 'Gurcke T, Alshomary M, Wachsmuth H. Assessing the Sufficiency of Arguments
    through Conclusion Generation. In: <i>Proceedings of the 8th Workshop on Argument
    Mining</i>. ; 2021:67-77.'
  apa: Gurcke, T., Alshomary, M., &#38; Wachsmuth, H. (2021). Assessing the Sufficiency
    of Arguments through Conclusion Generation. <i>Proceedings of the 8th Workshop
    on Argument Mining</i>, 67–77.
  bibtex: '@inproceedings{Gurcke_Alshomary_Wachsmuth_2021, title={Assessing the Sufficiency
    of Arguments through Conclusion Generation}, booktitle={Proceedings of the 8th
    Workshop on Argument Mining}, author={Gurcke, Timon and Alshomary, Milad and Wachsmuth,
    Henning}, year={2021}, pages={67–77} }'
  chicago: Gurcke, Timon, Milad Alshomary, and Henning Wachsmuth. “Assessing the Sufficiency
    of Arguments through Conclusion Generation.” In <i>Proceedings of the 8th Workshop
    on Argument Mining</i>, 67–77, 2021.
  ieee: T. Gurcke, M. Alshomary, and H. Wachsmuth, “Assessing the Sufficiency of Arguments
    through Conclusion Generation,” in <i>Proceedings of the 8th Workshop on Argument
    Mining</i>, 2021, pp. 67–77.
  mla: Gurcke, Timon, et al. “Assessing the Sufficiency of Arguments through Conclusion
    Generation.” <i>Proceedings of the 8th Workshop on Argument Mining</i>, 2021,
    pp. 67–77.
  short: 'T. Gurcke, M. Alshomary, H. Wachsmuth, in: Proceedings of the 8th Workshop
    on Argument Mining, 2021, pp. 67–77.'
date_created: 2021-10-04T12:38:02Z
date_updated: 2022-05-06T08:48:51Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.argmining-1.7.pdf
page: 67 - 77
project:
- _id: '52'
  name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 8th Workshop on Argument Mining
status: public
title: Assessing the Sufficiency of Arguments through Conclusion Generation
type: conference
user_id: '52174'
year: '2021'
...
---
_id: '23709'
author:
- first_name: Wei-Fan
  full_name: Chen, Wei-Fan
  id: '82920'
  last_name: Chen
- first_name: Khalid
  full_name: Al Khatib, Khalid
  last_name: Al Khatib
- first_name: Benno
  full_name: Stein, Benno
  last_name: Stein
- first_name: Henning
  full_name: Wachsmuth, Henning
  id: '3900'
  last_name: Wachsmuth
citation:
  ama: 'Chen W-F, Al Khatib K, Stein B, Wachsmuth H. Controlled Neural Sentence-Level
    Reframing of News Articles. In: <i>Findings of the Association for Computational
    Linguistics: EMNLP 2021</i>. ; 2021:2683-2693.'
  apa: 'Chen, W.-F., Al Khatib, K., Stein, B., &#38; Wachsmuth, H. (2021). Controlled
    Neural Sentence-Level Reframing of News Articles. <i>Findings of the Association
    for Computational Linguistics: EMNLP 2021</i>, 2683–2693.'
  bibtex: '@inproceedings{Chen_Al Khatib_Stein_Wachsmuth_2021, title={Controlled Neural
    Sentence-Level Reframing of News Articles}, booktitle={Findings of the Association
    for Computational Linguistics: EMNLP 2021}, author={Chen, Wei-Fan and Al Khatib,
    Khalid and Stein, Benno and Wachsmuth, Henning}, year={2021}, pages={2683–2693}
    }'
  chicago: 'Chen, Wei-Fan, Khalid Al Khatib, Benno Stein, and Henning Wachsmuth. “Controlled
    Neural Sentence-Level Reframing of News Articles.” In <i>Findings of the Association
    for Computational Linguistics: EMNLP 2021</i>, 2683–93, 2021.'
  ieee: 'W.-F. Chen, K. Al Khatib, B. Stein, and H. Wachsmuth, “Controlled Neural
    Sentence-Level Reframing of News Articles,” in <i>Findings of the Association
    for Computational Linguistics: EMNLP 2021</i>, 2021, pp. 2683–2693.'
  mla: 'Chen, Wei-Fan, et al. “Controlled Neural Sentence-Level Reframing of News
    Articles.” <i>Findings of the Association for Computational Linguistics: EMNLP
    2021</i>, 2021, pp. 2683–93.'
  short: 'W.-F. Chen, K. Al Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association
    for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.'
date_created: 2021-09-02T20:09:20Z
date_updated: 2022-05-09T15:00:09Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://aclanthology.org/2021.findings-emnlp.228.pdf
page: 2683 - 2693
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: 'Findings of the Association for Computational Linguistics: EMNLP 2021'
status: public
title: Controlled Neural Sentence-Level Reframing of News Articles
type: conference
user_id: '82920'
year: '2021'
...