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Data Science Centre Data Science Centre

Dr. S. (Sandro) Pezzelle

Faculty of Science
ILLC
Visiting address
  • Science Park 900
  • Room number: L6.55
Postal address
  • Postbus 94242
    1090 GE Amsterdam
Contact details
  • Publications

    2025

    • Bai, Y., & Pezzelle, S. (2025). If I feel smart, I will do the right thing: Combining Complementary Multimodal Information in Visual Language Models. In W. E. Zhang, X. Dai, D. Elliott, B. Fang, M. Sim, H. Zhuang, & W. Chen (Eds.), The Workshop of Evaluation of Multi-Modal Generation : proceedings of the First Workshop of Evaluation of Multi-Modal Generation: EvalMG 2025 : January, 2025 (pp. 24-39). Association for Computational Linguistics. https://aclanthology.org/2025.evalmg-1.3/ [details]

    2024

    • Hanna, M. W., Pezzelle, S., & Belinkov, Y. (2024). Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms. In Proceedings of COLM 2024 https://openreview.net/pdf?id=TZ0CCGDcuT
    • Mehrparvar, B., & Pezzelle, S. (2024). Detecting and Translating Language Ambiguity with Multilingual LLMs. In J. Sälevä, & A. Owodunni (Eds.), The 4th Workshop on Multilingual Representation Learning : proceedings of the workshop: MRL 2024 : November 16, 2024 (pp. 310–323). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.mrl-1.26 [details]
    • Surikuchi, A. K., Fernández, R., & Pezzelle, S. (2024). Not (yet) the whole story: Evaluating Visual Storytelling Requires More than Measuring Coherence, Grounding, and Repetition. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Findings of EMNLP 2024: EMNLP 2024 : November 12-16, 2024 (pp. 11597–11611). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.679 [details]
    • Takmaz, E., Pezzelle, S., & Fernández, R. (2024). Describing Images Fast and Slow: Quantifying and Predicting the Variation in Human Signals during Visuo-Linguistic Processes. In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics : Proceedings of the Conference: EACL 2024 : March 17-22, 2024 (Vol. 1, pp. 2072-2087). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-long.126 [details]
    • Testoni, A., Sprott, J., & Pezzelle, S. (2024). Naming, Describing, and Quantifying Visual Objects in Humans and LLMs. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) : proceedings of the conference: ACL 2024 : August 11-16, 2024 (Vol. 2, pp. 547-557). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-short.50 [details]
    • Wildenburg, F., Hanna, M., & Pezzelle, S. (2024). Do Pre-Trained Language Models Detect and Understand Semantic Underspecification? Ask the DUST!. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics : Findings of the Association for Computational Linguistics: ACL 2024: ACL 2024 : August 11-16, 2024 (pp. 9598-9613). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2402.12486, https://doi.org/10.18653/v1/2024.findings-acl.572 [details]

    2023

    • Buijtelaar, L., & Pezzelle, S. (2023). A Psycholinguistic Analysis of BERT's Representations of Compounds. In A. Vlachos, & I. Augenstein (Eds.), The 17th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2023 : proceedings of the conference : May 2-6, 2023 (pp. 2230–2241). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2302.07232, https://doi.org/10.18653/v1/2023.eacl-main.163 [details]
    • Chen, X., Fernández, R., & Pezzelle, S. (2023). The BLA Benchmark: Investigating Basic Language Abilities of Pre-Trained Multimodal Models. In H. Bouamar, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 5817–5830). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.356 [details]
    • Hanna, M., Belinkov, Y., & Pezzelle, S. (2023). When Language Models Fall in Love: Animacy Processing in Transformer Language Models. In H. Bouamar, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 12120-12135). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.744 [details]
    • Pezzelle, S. (2023). Dealing with Semantic Underspecification in Multimodal NLP. In A. Rogers, J. Boyd-Graper, & N. Okazaki (Eds.), The 61st Conference of the Association for Computational Linguistics: ACL 2023 : Proceedings of the Conference : July 9-14, 2023 (Vol. 1, pp. 12098-12112). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-long.675 [details]
    • Pezzelle, S., & Fernández, R. (2023). Semantic Adaptation to the Interpretation of Gradable Adjectives via Active Linguistic Interaction. Cognitive Science, 47(2), Article e13248. https://doi.org/10.1111/cogs.13248 [details]
    • Surikuchi, A., Pezzelle, S., & Fernández, R. (2023). GROOViST: A Metric for Grounding Objects in Visual Storytelling. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 3331-3339). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.202 [details]
    • Takmaz, E., Brandizzi, N., Giulianelli, M., Pezzelle, S., & Fernández, R. (2023). Speaking the Language of Your Listener: Audience-Aware Adaptation via Plug-and-Play Theory of Mind. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp. 4198-4217). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.258 [details]

    2022

    • Jansen, L., Laichter, Š. L., Sinclair, A., van der Goot, M. J., Fernández, R., & Pezzelle, S. (2022). Controllable Text Generation for All Ages: Evaluating a Plug-and-Play Approach to Age-Adapted Dialogue. In A. Bosselut, K. Chandu, K. Dhole, V. Gangal, S. Gehrmann, Y. Jernite, J. Novikova, & L. Perez-Beltrachini (Eds.), 2nd Workshop on Natural Language Generation, Evaluation and Metrics: GEM 2022 : proceedings of the workshop : December 7, 2022 (pp. 172-188). Association for Computational Linguistics. https://doi.org/https://aclanthology.org/2022.gem-1.14 [details]
    • Takmaz, E., Pezzelle, S., & Fernández, R. (2022). Less Descriptive yet Discriminative: Quantifying the Properties of Multimodal Referring Utterances via CLIP. In E. Chersoni, N. Hollenstein, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022 (pp. 36-42). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.cmcl-1.4 [details]

    2021

    • Bernardi, R., & Pezzelle, S. (2021). Linguistic issues behind visual question answering. Language and Linguistics Compass, 15(6), Article e12417. https://doi.org/10.1111/lnc3.12417 [details]
    • Jansen, L., Sinclair, A., van der Goot, M. J., Fernández, R., & Pezzelle, S. (2021). Detecting age-related linguistic patterns in dialogue: Toward adaptive conversational systems. In E. Fersini, M. Passarotti, & V. Patti (Eds.), Proceedings of the Eighth Italian Conference on Computational Linguistics: Milan, Italy, June 29-July 1, 2022 Article 47 (CEUR Workshop Proceedings; Vol. 3033). CEUR-WS. https://ceur-ws.org/Vol-3033/paper47.pdf [details]
    • Jolly, S., Pezzelle, S., & Nabi, M. (2021). EaSe: A Diagnostic Tool for VQA Based on Answer Diversity. In K. Toutanova, A. Rumshisky, L. Zettlemoyer, D. Hakkani-Tur, I. Beltagy, S. Bethard, R. Cotterell, T. Chakraborty, & Y. Zhou (Eds.), The 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL-HLT 2021 : proceedings of the conference : June 6-11, 2021 (pp. 2407-2414). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.naacl-main.192 [details]
    • Parfenova, I., Elliott, D., Fernández, R., & Pezzelle, S. (2021). Probing Cross-Modal Representations in Multi-Step Relational Reasoning. In A. Rogers, I. Calixto, I. Vulić, N. Saphra, N. Kassner, O.-M. Camburu, T. Bansal, & V. Shwartz (Eds.), The 6th Workshop on Representation Learning for NLP: RepL4NLP 2021 : proceedings of the workshop : August 6, 2021, Bangkok, Thailand (online) (pp. 152–162). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.repl4nlp-1.16 [details]
    • Pezzelle, S. (Ed.) (2021). Identifying, Analyzing, and Overcoming Challenges in Vision and Language Research. Frontiers Research Topics.
    • Pezzelle, S., Takmaz, E., & Fernández, R. (2021). Word Representation Learning in Multimodal Pre-Trained Transformers: An Intrinsic Evaluation. Transactions of the Association of Computational Linguistics, 9, 1563–1579. https://doi.org/10.1162/tacl_a_00443 [details]

    2020

    • Gualdoni, E., Bernardi, R., Fernández, R., & Pezzelle, S. (2020). Grounded and Ungrounded Referring Expressions in Human Dialogues: Language Mirrors Different Grounding Conditions. In J. Monti, F. Dell'Orletta, & F. Tamburini (Eds.), Proceedings of the Seventh Italian Conference on Computational Linguistics: Bologna, Italy, March 1-3, 2021 Article 38 (CEUR Workshop Proceedings; Vol. 2769). CEUR-WS. http://ceur-ws.org/Vol-2769/paper_38.pdf [details]
      • Related datasets
        • Fernández, R., Pezzelle, S., Sinclair, A., Takmaz, E., Giulianelli, M., Gelderloos, L., Calixto, I., Bruni, E., Haber, J., Bernardi, R. B. & Baumgärtner, T. (2019). The PhotoBook Task and Dataset. GitHub. https://dmg-photobook.github.io/
    • Pezzelle, S., & Marelli, M. (2020). Do semantic features capture a syntactic classification of compounds? Insights from compositional distributional semantics. In S. Schulte im Walde, & E. Smolka (Eds.), The role of constituents in multiword expressions: An interdisciplinary, cross-lingual perspective (pp. 33-60). (Phraseology and Multiword Expressions; Vol. 4). Language Science Press. https://doi.org/10.5281/zenodo.3598556 [details]
    • Pezzelle, S., Greco, C., Gandolfi, G., Gualdoni, E., & Bernardi, R. (2020). Be Different to Be Better!: A Benchmark to Leverage the Complementarity of Language and Vision. In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics : Findings of ACL: EMNLP 2020: 16-20 November, 2020 (pp. 2751-2767). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.findings-emnlp.248 [details]
    • Takmaz, E., Giulianelli, M., Pezzelle, S., Sinclair, A., & Fernández, R. (2020). Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 4350-4368). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.353 [details]
      • Related datasets
        • Fernández, R., Pezzelle, S., Sinclair, A., Takmaz, E., Giulianelli, M., Gelderloos, L., Calixto, I., Bruni, E., Haber, J., Bernardi, R. B. & Baumgärtner, T. (2019). The PhotoBook Task and Dataset. GitHub. https://dmg-photobook.github.io/
    • Takmaz, E., Pezzelle, S., Beinborn, L., & Fernández, R. (2020). Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 4664–4677). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.377 [details]

    2019

    • Pezzelle, S., & Fernández, R. (2019). Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size. In A. Mogadala, D. Klakow, S. Pezzelle, & M.-F. Moens (Eds.), Beyond Vision and LANguage: inTEgrating Real-world kNowledge (LANTERN): EMNLP-IJCNLP 2019 : proceedings of the workshop : November 3, 2019, Hong Kong, China (pp. 18-23). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-6403 [details]
    • Pezzelle, S., & Fernández, R. (2019). Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts. In K. Inui, J. Jiang, V. Ng, & X. Wan (Eds.), 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing: EMNLP-IJCNLP 2019 : proceedings of the conference : November 3-7, 2019, Hong Kong, China (pp. 2865-2876). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1285 [details]
    • Testoni, A., Pezzelle, S., & Bernardi, R. (2019). Quantifiers in a Multimodal World: Hallucinating Vision with Language and Sound. In E. Chersoni, C. Jacobs, A. Lenci, T. Linzen, L. Prévot, & E. Santus (Eds.), Cognitive Modeling and Computational Linguistics: NAACL HLT 2019 : proceedings of the workshop : June 7, 2019, Minneapolis, USA (pp. 105-116). The Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-2912 [details]

    2018

    • Pezzelle, S., Steinert Threlkeld, S., Bernardi, R., & Szymanik, J. (2018). Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers. In I. Gurevych, & Y. Miyao (Eds.), ACL 2018 : The 56th Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : July 15-20, 2018, Melbourne, Australia (Vol. 2, pp. 114-119). The Association for Computational Linguistics. https://doi.org/10.18653/v1/P18-2019 [details]

    2016

    • Paperno, D., Kruszewski, G., Lazaridou, A., Pham, Q. N., Bernardi, R., Pezzelle, S., Baroni, M., Boleda, G., & Fernández, R. (2016). The LAMBADA dataset: Word prediction requiring a broad discourse context. In K. Erk, & N. A. Smith (Eds.), The 54th Annual Meeting of the Association for Computational Linguistics : ACL 2016: proceedings of the conference : August 7-12, 2016, Berlin Germany (Vol. 1, pp. 1525-1534). Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-1144 [details]

    2022

    • Jansen, L. (Author), Laichter, Š. L. (Author), Sinclair, A. (Author), van der Goot, M. J. (Author), Fernandez Rovira, R. (Author), & Pezzelle, S. (Author). (2022). Exploring Age Adaptation of Conversational Systems. Web publication or website https://dmg-illc.github.io/ai-age-adaptation/

    2023

    • van der Goot, M. J., Dolinšek, S., Jansen, L., Sinclair, A. J., Fernandez Rovira, R., & Pezzelle, S. (2023). Adapting the language of conversational systems to different age groups: An experimental study. Paper presented at Etmaal van de Communicatiewetenschap, Enschede.

    2022

    • Takmaz, E., Pezzelle, S., & Fernandez Rovira, R. (2022). Time Alignment between Gaze and Speech in Image Descriptions: Exploring Theories of Linearization. Abstract from 44th Annual Meeting of the Cognitive Science Society. https://escholarship.org/uc/item/83w56904

    2021

    • Jansen, L., Sinclair, A. J., van der Goot, M. J., Fernandez Rovira, R., & Pezzelle, S. (2021). Detecting age-related linguistic patterns in dialogue: Toward adaptive conversa-tional systems. Paper presented at CLIC-it 2021: Eighth Italian Conference on Computational Linguistics , Milan, Italy.
    • van der Goot, M. J., Georgiou, M., Dolinšek, Š., Jansen, L., Sinclair, A. J., Fernández, R., & Pezzelle, S. (2021). Exploring the potential of adapting conversational systems to different age groups: A pilot study. Paper presented at Conversations 2021. https://conversations2021.files.wordpress.com/2021/11/conversations_2021_positionpaper_20_vandergoot-1.pdf

    2020

    Prize / grant

    • Cinà, G. & Pezzelle, S. (2023). UvA Interfaculty Seed grant.
    • Pezzelle, S., Fernández, R. & van der Goot, M. (2020). Exploring Adaptation of Conversational Systems to Different Age Groups.

    Journal editor

    • Pezzelle, S. (editor), Klakow, D. (editor), Akata, Z. (editor), Moens, M.-F. (editor), Mosbach, M. (editor) & Hedderich, M. (editor) (2021). The Third Workshop Beyond Vision and LANguage: inTEgrating Real-world kNowledge (Event). https://www.lantern.uni-saarland.de/2021/
    • Pezzelle, S. (editor), Mogadala, A. (editor), Klakow, D. (editor), Moens, M.-F. (editor) & Akata, Z. (editor) (2020). The Second Workshop Beyond Vision and LANguage: inTEgrating Real-world kNowledge (Event). https://www.lantern.uni-saarland.de/2020/
    • Pezzelle, S. (editor), Mogadala, A. (editor), Klakow, D. (editor) & Moens, M.-F. (editor) (2019). The First Workshop Beyond Vision and LANguage:inTEgrating Real-world kNowledge (LANTERN) (Event), Hong Kong. https://www.lantern.uni-saarland.de/

    Talk / presentation

    • Pezzelle, S. (speaker) (28-11-2024). Not (yet) the whole story: The need for human-like evaluation of visual LLMs in multimodal communicative tasks, Fine-grained Evaluation of Vision and Language Models workshop, Bozen.
    • Pezzelle, S. (speaker) (24-10-2024). Implicit and Underspecified Language as a Communicative Testbed for Large Language Models, Dealing with Meaning Variation in NLP 2024, Utrecht.
    • Pezzelle, S. (speaker) (18-10-2024). Gen-AI and the future of HRM: Open challenges from NLP, Generative AI in the Future of HRM, Amsterdam.
    • Pezzelle, S. (speaker) (1-10-2024). Implicit and Underspecified Language as a Communicative Testbed for Large Language Models, Perspectives in NLP x Humanities, Cognition, and Social Sciences, Aarhus.
    • Pezzelle, S. (speaker) (13-9-2024). Leveraging gaze data in image description generation: Towards more human-like visually-grounded NLP models, MultiplEYE Mid-Term Conference 2024, Tirana.
    • Pezzelle, S. (speaker) (15-8-2024). From semantic understanding to human-like communication: Implicit and underspecified language as a testbed for large language models, 13th Edition of the Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2024, Bangkok.
    • Pezzelle, S. (speaker) (24-5-2024). Dealing with implicit and underspecified language: A semantic challenge for large language models, Tilburg University.
    • Pezzelle, S. (speaker) (23-4-2024). Large Language Models as Interlocutors: Between Reliability and Deconstruction, Uva AI x Cultural Production Seminar, Amsterdam.
    • Pezzelle, S. (speaker) (5-4-2024). From NLP to General Intelligence: Directions and Open Challenges, Fluido.
    • Pezzelle, S. (speaker) (13-3-2024). From Word Representation to Communicative Success: Beyond Image-Text Alignment in Language-and-Vision Modeling, Heriot-Watt University.
    • Pezzelle, S. (speaker) (28-2-2024). Dealing with implicit and underspecified language: A semantic challenge for large language models, COLT Seminar at UPF, Barcelona, Barcelona.
    • Pezzelle, S. (speaker) (26-2-2024). Dealing with implicit and underspecified language: A semantic challenge for large language models, Amazon Science Barcelona.
    • Pezzelle, S. (speaker) (25-1-2024). A Psycholinguistic Analysis of BERT's Representations of Compounds, Using computational models to bridge between neurobiology, psychology, and linguistic theory workshop, Nijmegen.
    • Pezzelle, S. (speaker) (11-1-2024). A Psycholinguistic Analysis of BERT's Representations of Compounds, HumanCLAIM workshop, Amsterdam.
    • Pezzelle, S. (speaker) (23-11-2022). Controllable Text Generation for All Ages: Evaluating a Plug-and-Play Approach to Age-Adapted Dialogue, Conversations 2022: 6th international workshop on chatbot research.
    • Pezzelle, S. (speaker) (30-6-2022). Detecting Age-Related Linguistic Patterns in Dialogue: Toward Adaptive Conversational Systems, Eighth Italian Conference on Computational Linguistics, Milan.
    • Pezzelle, S. (speaker) (22-6-2022). Modeling gradable adjectives leveraging visual contexts, University of Milano-Bicocca.
    • Pezzelle, S. (speaker) (23-5-2022). Word Representation Learning in Multimodal Pre-Trained Transformers: An Intrinsic Evaluation, 60th Annual Meeting of the Association for Computational Linguistics, Dublin.
    • Pezzelle, S. (speaker) (17-5-2022). Semantic adaptation through active information seeking: A case study on gradable adjectives, CoSaQ final workshop, Amsterdam.
    • Pezzelle, S. (speaker) (7-3-2022). Visually-grounded semantics in multimodal Transformers (and humans), Center for Mind/Brain Sciences, CIMeC, University of Trento, Rovereto, Italy..
    • Pezzelle, S. (speaker) (14-12-2021). Visually-grounded semantics in deep neural networks (and humans).
    • Pezzelle, S. (speaker) (21-6-2021). Integration of language and vision in multimodal pre-trained Transformers.
    • Pezzelle, S. (speaker) (7-5-2021). Semantic adaptation to the interpretation of gradable adjectives via passive exposure and active information seeking.
    • Pezzelle, S. (speaker) (18-3-2021). Be Different to Be Better! A Benchmark to Leverage the Complementarity of Language and Vision, TAB meeting.
    • Pezzelle, S. (speaker) (25-2-2021). Be Different to Be Better! A Benchmark to Leverage the Complementarity of Language and Vision, ELLIS NLP Workshop.

    Others

    • Pezzelle, S. (visiting researcher) (19-2-2024 - 1-3-2024). Universitat Pompeu Fabra (UPF) (visiting an external institution).
    • Pezzelle, S. (visiting researcher) (4-4-2022 - 15-4-2022). Center for Mind/Brain Sciences, CIMeC, University of Trento, Rovereto, Italy. (visiting an external institution).
    • Pezzelle, S. (organiser) (20-4-2021). The Third Workshop Beyond Vision and LANguage: inTEgrating Real-world kNowledge (organising a conference, workshop, ...).
    • Pezzelle, S. (organiser), Mogadala, A. (organiser), Klakow, D. (organiser), Moens, M.-F. (organiser) & Akata, Z. (organiser) (13-12-2020). The Second Workshop Beyond Vision and LANguage: inTEgrating Real-world kNowledge (organising a conference, workshop, ...). https://www.lantern.uni-saarland.de/2020/overview/
    • Pezzelle, S. (organiser), Mogadala, A. (organiser), Klakow, D. (organiser) & Moens, M.-F. (organiser) (3-11-2019). The First Workshop Beyond Vision and LANguage:inTEgrating Real-world kNowledge (LANTERN), Hong Kong (organising a conference, workshop, ...). https://www.lantern.uni-saarland.de/

    2024

    • Takmaz, E. K. (2024). Visual and linguistic processes in deep neural networks: A cognitive perspective. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2025

    • Bavaresco, A., de Heer Kloots, M., Pezzelle, S., Fernández, R., Bavaresco, A., de Heer Kloots, M., Pezzelle, S. & Fernández, R. (15-4-2025). Modelling Multimodal Integration in Human Concept Processing with Vision-Language Models. Zenodo. https://doi.org/10.5281/zenodo.15221180

    2023

    2021

    2019

    2016

    • Paperno, D., Kruszewski, G., Lazaridou, A., Pham, Q., Bernardi, R. B., Pezzelle, S., Baroni, M., Boleda, G. & Fernández, R. (2016). The LAMBADA dataset. Zenodo. https://doi.org/10.5281/zenodo.2630551
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  • Ancillary activities
    • IVADO Labs
      Scientific advisor for AI projects.
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