Publications in Journals

  1. E. Mariotti (ESR1-CiTIUS-USC), A. Arias Duart, M. Cafagna (ESR5-UOM), A. Gatt, D. Garcia-Gasulla, M. J. Alonso, “TextFocus: Assessing the Faithfulness of Feature Attribution Methods Explanations in Natural Language Processing,” IEEE Access, 2023, https://doi.org/10.1109/ACCESS.2023.10543008
  2. A. Rieger (ESR10-TUDelft), T. Draws, M. Theune, N. Tintarev, «Nudges to Mitigate Confirmation Bias during Web Search on Debated Topics: Support vs. Manipulation», ACM Transactions on the Web, Volume 18, Issue 2, Article No.: 27, pp 1–27, 2024, https://doi.org/10.1145/3635034
  3. L. Nannini (ESR11-INDRA), E. Bonel, D. Bassi, M. Joshua, «Beyond phase-in: assessing impacts on disinformation of the EU Digital Services Act», AI and Ethics, 2024, https://doi.org/10.1007/s43681-024-00467-w
  4. L. Nannini (ESR11-INDRA), J. Alonso Moral, A. Catala, M. Penin, S. Barro, «Operationalizing Explainable AI in the EU Regulatory Ecosystem», IEEE Intelligent Systems, 2024, https://doi.org/10.5281/zenodo.10792499
  5. E. Mariotti (ESR1-INDRA), J. Alonso Moral, A. Gatt, «Exploring the balance between interpretability and performance with carefully designed constrainable Neural Additive Models», Information Fusion, 2023, http://doi.org/10.1016/j.inffus.2023.101882
  6. M. Cafagna (ESR5-UOM), L. M. Rojas-Barahona, K. van Deemter, A. Gatt, «Interpreting vision and language generative models with semantic visual priors», Frontiers in Artificial Intelligence, 2023, http://doi.org/10.3389/frai.2023.1220476
  7. T. Di Noia, N. Tintarev, P. Fatourou, M. Schedl, «Recommender systems under European AI regulation», Communications of the ACM, Volume 65, Issue 4, 2022, http://doi.org/10.1145/3512728

Publications in Conferences

  1.  A. Sivaprasad (ESR9-UTWENTE), E. Reiter, N. Tintarev, N. Oren, “Evaluation of Human-Understandability of Global Model Explanations using Decision Tree,” ECAI 2023: Proceedings of the European Conference on Artificial Intelligence, 2023, Pages 45–58, https://doi.org/10.1007/978-3-031-50396-2_3
  2. A. Sivaprasad (ESR9-UTWENTE), E. Reiter, “Linguistically Communicating Uncertainty in Patient-Facing Risk Prediction Models,” EACL 2024: Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics, 2024, Pages 87–99, https://doi.org/10.48550/arXiv.2401.17511

  3. A. Rieger (ESR10-TUDelft), F. Bredius, M. Theune, M. Pera, «From Potential to Practice: Intellectual Humility During Search on Debated Topics», CHIIR ’24: Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, March 2024, Pages 130–141, https://doi.org/10.1145/3627508.3638306
  4.       A. Rieger (ESR10-TUDelft), T. Draws, N. Mattis, D. Maxwell, D. Elsweiler, U. Gadiraju, D. McKay, A. Bozzon, M. Pera, «Responsible Opinion Formation on Debated Topics in Web Search», European Conference on Information Retrieval, 2024, https://doi.org/10.1007/978-3-031-56066-8_32
  5.       E. Mariotti (ESR1-CiTIUS-USC), A. Sivaprasad, J. Alonso, «Beyond Prediction Similarity: ShapGAP for Evaluating Faithful Surrogate Models in XAI», World Conference on Explainable Artificial Intelligence, 2023, https://link.springer.com/chapter/10.1007/978-3-031-44064-9_10
  6.       H. Zhang (ESR8-WUT), «Emotion-based profiles of political leaders on Twitter», 8th International Conference on Philosophy of Language and Linguistics, PhiLang 2023, May 12-14, 2023
  7.       E. Calò (ESR4-UTRECHT), J. Levy, «General Boolean Formula Minimization with QBF Solvers», 25th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2023), 2023, https://doi.org/10.48550/arXiv.2303.06643
  8.       A. Rieger (ESR10-TUDelft), F. Bredius, N. Tintarev, M. Pera, «Searching for the Whole Truth: Harnessing the Power of Intellectual Humility to Boost Better Search on Debated Topics», Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 2023, http://doi.org/10.1145/3544549.3585693
  9.       E. Calò (ESR4-UTRECHT), J. Levy, A. Gatt, K. van Deemter, «Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation», Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), 2023, http://doi.org/10.5281/zenodo.8246480
  10.       T. Mickus, E. Calò (ESR4-UTRECHT), L. Jacqmin, D. Paperno, M. Constant, «„Mann“ is to “Donna” as「国王」is to « Reine » Adapting the Analogy Task for Multilingual and Contextual Embeddings», Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), 2023, http://dx.doi.org/10.18653/v1/2023.starsem-1.25
  11.       L. Nannini (ESR11-CiTIUS-USC), A. Balayn, A. Smith, «Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UK», Proceedings, 2023, http://doi.org/10.1145/3593013.3594074
  12.   S. Srivastava (ESR9-UTWENTE), M. Theune, A. Catala, «The Role of Lexical Alignment in Human Understanding of Explanations by Conversational Agents», Proceedings of the 28th International Conference on Intelligent User Interfaces, 2023, https://doi.org/10.1145/3581641.3584086
  13.   A. Arias-Duart, E. Mariotti (ESR1-CiTIUS-USC), D. Garcia-Gasulla, J. Alonso-Moral, «A Confusion Matrix for Evaluating Feature Attribution Methods», 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023, https://doi.org/10.1109/CVPRW59228.2023.00380
  14.   M. Cafagna (ESR5-UOM), K. van Deemter, A. Gatt, «HL Dataset: Visually-Grounded Description of Scenes, Actions and Rationales», 16th International Natural Language Generation Conference, 2023, https://doi.org/10.18653/v1/2023.inlg-main.21
  15.   H. Zhang (ESR8-WUT), «Trust analytics in digital rhetoric», European Conference on Argumentation (ECA 2023), September 28-30, 2022
  16.   M. Cafagna (ESR5-UOM), K. van Deemter, A. Gatt, «Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions», The first Unimodal and Multimodal Induction of Linguistic Structures Workshop (UM-IoS) at the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), 2022, http://doi.org/10.5281/zenodo.7669908
  17.   E. Calò (ESR4-UTRECHT), E. van der Werf, A. Gatt, K. van Deemter, «Enhancing and Evaluating the Grammatical Framework Approach to Logic-to-Text Generation», Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), 2022, http://dx.doi.org/10.18653/v1/2022.gem-1.13
  18.   A. Rieger (ESR10-TUDelft), «Interactive Interventions to Mitigate Cognitive Bias», Doctoral Consortium at Conference on User Modeling, Adaptation and Personalization 2022, July 04th to 07th 2022, https://doi.org/10.1145/3503252.3534362
  19.   L. Parcalabescu, M. Cafagna (ESR5-UOM), L. Muradjan, A. Frank, I. Calixto, A. Gatt, «VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena», Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022, http://doi.org/10.18653/v1/2022.acl-long.567
  20.   A. Bringas Colmenarejo, L. Nannini (ESR11-INDRA), A. Rieger (ESR10-TUDelft), X. Zhao, G. Patro, G. Kasneci, K. Kinder-Kurlanda, «Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation», Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2022, http://doi.org/10.1145/3514094.3534158
  21.   A. Rieger (ESR10-TUDelft), Q. Shaheen, C. Sierra, M. Theune, N. Tintarev, «Towards Healthy Engagement with Online Debates: An Investigation of Debate Summaries and Personalized Persuasive Suggestions», UMAP ’22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, July 2022, https://doi.org/10.1145/3511047.3537692
  22.   J. Faille (ESR6-CNRS), A. Gatt, C. Gardent, «Entity-Based Semantic Adequacy for Data-to-Text Generation», Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, https://doi.org/10.18653/v1/2021.findings-emnlp.132
  23.   A. Rieger (ESR10-TUDelft), T. Draws, M. Theune, N. Tintarev, «This Item Might Reinforce Your Opinion: Obfuscation and Labeling of Search Results to Mitigate Confirmation Bias», Proceedings of the 32st ACM Conference on Hypertext and Social Media, 2021, https://doi.org/10.1145/3465336.3475101
  24.   E. Mariotti (ESR1-CiTIUS-USC), J. Alonso, A. Gatt, «Prometheus: Harnessing Natural Language for Human-centric Explainable Artificial Intelligence», Proceedings of CAEPIA’21, Actas del XX Congreso Español sobre Tecnologías y Lógica Fuzzy, pp. 274-279, Málaga, 2021, https://doi.org/10.5281/zenodo.5878570
  25.   E. Mariotti (ESR1-CiTIUS-USC), J. Alonso, R. Confalonieri, «A Framework for Analyzing Fairness, Accountability, Transparency and Ethics: A Use-case in Banking Services», Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Luxembourg, 2021, https://doi.org/10.1109/fuzz45933.2021.9494481
  26.   L. Parcalabescu, A. Gatt, A. Frank, I. Calixto, «Seeing past words: Testing the cross-modal capabilities of pretrained V&L models on counting tasks», 1st Workshop on Multimodal Semantic Representations (MMSR), 2021, https://aclanthology.org/2021.mmsr-1.4
  27.   E. Calò (ESR4-UTRECHT), J. Levy, A. Gatt, K. van Deemter, «Enhancing and Evaluating the Grammatical Framework Approach to Logic-to-Text Generation», Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), 2022, http://dx.doi.org/10.18653/v1/2022.gem-1.13
  28.   J. Sevilla (ESR3-UNIABDN), «Explaining data using causal Bayesian networks», Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI), collocated with the 12th International Conference on Natural Language Generation (INLG), Dublin, Ireland, 2020, ACL anthology, https://doi.org/10.5281/zenodo.5897993
  29.   M. Demollin (ESR8-WUT), Q. Shaheen, K. Budzynska, C. Sierra, «Argumentation Theoretical Frameworks for Explainable Artificial Intelligence», 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI2020), 2020, https://doi.org/10.5281/zenodo.5886641
  30.   J. Faille (ESR6-CNRS), A. Gatt, C. Gardent, «The Natural Language Pipeline, Neural Text Generation and Explainability», 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence, 2020, https://doi.org/10.5281/zenodo.5887676
  31.   C. Hennessy (ESR2-CiTIUS-USC), A. Bugarín-Diz, E. Reiter, «Explaining Bayesian Networks in Natural Language: State of the Art and Challenges», Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI), collocated with the 12th International Conference on Natural Language Generation (INLG), Dublin, Ireland, 2020, ACL anthology, https://doi.org/10.5281/zenodo.5882297
  32.   A. Mayn (ESR4-UU), K. van Deemter, «Towards Generating Effective Explanations of Logical Formulas: Challenges and Strategies», Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI), collocated with the 12th International Conference on Natural Language Generation (INLG), Dublin, Ireland, 2020, ACL anthology, https://doi.org/10.5281/zenodo.5906859
  33.   E. Mariotti (ESR1-CiTIUS-USC), J. Alonso, A. Gatt, «Towards Harnessing Natural Language Generation to Explain Black-box Models», Proceedings of the 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence, collocated with the 12th International Conference on Natural Language Generation (INLG), Dublin, Ireland, 2020, ACL anthology, https://doi.org/10.5281/zenodo.5876893

Posters

  1. S. Wentzel, M. Theune, S. Srivastava, D. Bucur, «Interplay between linguistic alignment and sentiment in online discussions», The 33rd Meeting of Computational Linguistics in The Netherlands, Antwerp, Belgium, 22 September 2023.
  2. L. Nannini, «Explainability in Process Mining: A Framework for Improved Decision-Making», AAAI/ACM AIES 2023, student track presentation and workshop attendance, Montreal, 8-10 August 2023.
  3. S. Srivastava, «Personalized Explanations by Conversational Agents using Lexical Alignment», Doctoral Consortium and the poster sessions of the conference Conversational User Interfaces 2023, July 19-21, 2023, Eindhoven, Netherlands. https://doi.org/10.5281/zenodo.8381519
  4. A. Rieger, F. Bredius, N. Tintarev, M. Pera, «Searching for the Whole Truth: Harnessing the Power of Intellectual Humility to Boost Better Search on Debated Topics», Late Breaking Poster at CHI Conference on Human Factors in Computing Systems, April 26th and 27th, 2023. https://doi.org/10.5281/zenodo.8382587
  5. S. Srivastava, M. Theune, A. Catala, «Role of Lexical Alignment in Human Understanding of Explanations by Conversational Agents», ICT.Open 2023 conference, April 19-20, 2023, Utrecht, The Netherlands. https://doi.org/10.5281/zenodo.8381515
  6. A. Rieger, «Boosting Intellectual Humility to Mitigate Confirmation Bias during Search on Debated Topics», NWO ICT.OPEN2023, April 20th 2023.

Videos

  • Showcasing NL4XAI

Research Projects and Achievements by Our Early Stage Researchers

  • ESR2 Research Results

Research Projects and Achievements by Our Early Stage Researchers

  • ESR7 Research Results

PhD title: Argumentation-based multi-agent recommender system

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  • ESR6 Research Results.

Case study: Entity-Based Semantic Adequacy for Data-to-Text Generation.

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  • Alisa RiegerESR10 Research Results.

Case study: This Item Might Reinforce Your Opinion: Obfuscation and Labeling of Search Results to Mitigate Confirmation Bias.

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  • Alisa Rieger, ESR10- TUDelft, Research Results.

Case study: Searching for the Whole Truth: Harnessing the Power of Intellectual Humility to Boost Better Search on Debated Topics

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  • Eduardo Calò, ESR5-UU, Research Results.

Case study: Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions

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  • Ettore Mariotti, ESR1-CiTIUS-USC, Research Results.

Case study: Explaining black box AI models

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  • Luca Nannini, ESR11-INDRA, Research Results.

Case study: Explainability in Process Mining A Framework for Improved Decision Making

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  • Nikolay Babakov, ESR2-CiTIUS-USC, Research Results.

Case study: Explainable AI and Bayesian Networks Development

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