2024
Bentum, M., ten Bosch, L., Lentz, T. The Processing of Stress in End-to-End Automatic Speech Recognition Models. In Proc. Interspeech 2024, pp. 2350-2354.
Edman, L, Sarti, G, Toral, A., van Noord, G., Bisazza, A. Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine Translation. In Transactions of the Association for Computational Linguistics,2024, 12: 392–410.
Ferrando, J., Sarti, G., Bisazza, A., Costa-jussa, M. A Primer on the Inner Workings of Transformer-based Language Models, 2024. [Pre-print]
Langedijk, A., Mohebbi, H., Sarti, G., Zuidema, W., Jumelet, J. DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers. In Findings of the Association for Computational Linguistics: NAACL 2024, (2024) 4764–4780.
Lian, Y., Verhoef, T., Bisazza, A. NeLLCom-X: A Comprehensive Neural-Agent Framework to Simulate Language Learning and Group Communication. In Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL), 2024, pp. 243–258.
Qi, J., Sarti, G., Fernández, R., Bisazza, A. Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025, pp. 6037-6053.
Sarti, G., Chrupała, G.,, Nissim, M., Bisazza, A. Quantifying the Plausibility of Context Reliance in Neural Machine Translation. In Proceedings of the Twelfth International Conference on Learning Representations,2024, 1-29.
Sarti, G., Feldhus, N., Qi, J., Nissim, M., Bisazza, A. Democratizing Advanced Attribution Analyses of Generative Language Models with the Inseq Toolkit. In Joint Proceedings of the Late-breaking Work, Demos and Doctoral Consortium of the 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024), 2024, 289-296.
Scalena, D., Sarti, G., Nissim, M. Multi-property Steering of Large Language Models with Dynamic Activation Composition. In Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, 2024, pp. 577–603.
Shen, G., Watkins, M., Alishahi, A., Bisazza, A., Chrupała, G. Encoding of Lexical Tone in Self-supervised Models of Spoken Language. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024, pp. 4250–4261.
Zhang, Y., Verhoef, T., van Noord, G., Bisazza, A. Endowing Neural Language Learners with Human-like Biases: A Case Study on Dependency Length Minimization. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, 2024, pp. 5819–5832.
2023
Beeksma, M, Hendrickx, I., Das, E. The International Encyclopedia of Health Communication, Chapter Text Mining. Wiley-Blackwell, 2023.
Bockting, C.L., Dis, van E.A.M., Rooij, van R., Zuidema, W., Bollen, J. Living guidelines for generative AI – why scientists must oversee its use. Nature. 2023; 622 (7984), 693-696.
Bosch, L. ten, Bentum, M., Boves, L. Phonemic competition in end-to-end ASR models. Proc of Interspeech 2023, pp. 586-590.
Burgoyne, J. A., Spijkervet, J., Baker, D.J. Measuring the Eurovision Song Contest: A living dataset for real-world MIR. In Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023, pp. 817–23.
Chintam, A., Beloch, R., Zuidema, W., Hanna, M., Wal, O. van der. Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model. 2023. In Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, pp. 379–394.
Chrupała, G. Putting Natural in Natural Language Processing. Findings of the ACL 2023, pp. 7820-7827.
Coretta, S., Casillas, J.V., Roessig, S., Lentz, T. O., et al. Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses. Advances in Methods and Practices in Psychological Science. 2023; 6 (3).
Cruz, J.A. dela, Hendrickx, I., Larson, M. Towards XAI for Information Ex- traction on Online Media Data for Disaster Risk Management. 2023. In Proceedings of the 20th International ISCRAM Conference, pp. 478–486.
Cruz, J.A. dela, Hendrickx, I., Larson, M. Understanding Fine-tuned BERT Models for Flood Location Extraction on Twitter Data. In Proceedings of MediaEval’22: Multimedia Evaluation Workshop, 2023.
Dis, E. A van., Bollen, J., Zuidema, W., Rooij, R. van, Bockting, C. L. (2023). ChatGPT: five priorities for research. Nature, 614 (7947), 224-226.
Hoeken, S., Alaçam, Ö., Fokkens, A., Sommerauer, P. 2023. Methodological Insights in Detecting Subtle Semantic Shifts with Contextualized and Static Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 3662-3675.
Huynh, M. H., Lentz, T., Miltenburg, E. van. Implicit causality in GPT-2: a case study. In: Proceedings of the 15th International Conference on Computational Semantics, 2023, pp. 67-77.
Jumelet, J., Zuidema, W. 2023. Feature Interactions Reveal Linguistic Structure in Language Models. In Findings of the Association for Computational Linguistics: ACL 2023, pp. 8697–8712.
Lian, Y., Bisazza, A., Verhoef, T. Communication Drives the Emergence of Language Universals in Neural Agents: Evidence from the Word-order/Case-marking Trade-off. Transactions of the Association for Computational Linguistics, 2023, 11: 1033–1047.
Kamp, J., Beinborn, L., Fokkens, A. Dynamic Top-k Estimation Consolidates Disagreement between Feature Attribution Methods. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023, pp. 6190-6197.
Mohebbi, H., Chrupała, G., Zuidema, W., Alishahi, A. 2023. Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023,pp. 8249–8260.
Mohebbi, H., Zuidema, W., Chrupała, G., Alishahi, A. Quantifying Context Mixing in Transformers. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pp. 3378–3400.
Pouw, C., Hollenstein, N., Beinborn, L. (2023). Cross-Lingual Transfer of Cognitive Processing Complexity. In Findings of the Association for Computational Linguistics: EACL 2023, pp. 655–669.
Sarti, G., Feldhus, N., Sickert, L., Wal, O. van der. Inseq: An Interpretability Toolkit for Sequence Generation Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), 2023, pp. 421–435.
Shen, G., Alishahi, A., Bisazza, A., Chrupała, G. (2023). Wave to Syntax: Probing spoken language models for syntax. Proc of Interspeech 2023, pp. 1259-1263.
Vélez Vásquez, M., Baelemans, M., Driedger, J., Zuidema, W., Burgoyne, J.A. Quantifying the ease of playing song chords on the guitar. In Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023, pp. 725–32.
Yang, X., Chen, J., Eerden, A. van, Mozib Samin, A., Bisazza, A. Slaapte or Sliep? Extending Neural-Network Simulations of English Past Tense Learning to Dutch and German. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), 2023, pp. 92–102.
2022
Adams, J., Poelmans, K., Hendrickx, I., Larson, M. Doing not Being: Concrete Language as a Bridge from Language Technology to Ethnically Inclusive Job Ads. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, 2022, pp. 19–25.
Bentum, M., Bosch, L. ten, Heuvel, H. van den, Wills, S., Niet, D. van der, Dijkstra, J., and Velde, H. van de. A. Speech Recognizer for Frisian/Dutch Council Meetings. Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022, pp.1009–1015.
Chrupała, G. Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques. Journal of Artificial Intelligence Research, 73, (2022), 673-707.
Haghighatkhah, P., A. Fokkens, A., Sommerauer, P., Speckmann, B., Verbeek, K. Better Hit the Nail on the Head than Beat around the Bush: Removing Protected Attributes with a Single Projection. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022, pp. 8395-8416.
Kamp, J., Beinborn, L., Fokkens, A. (2022). Perturbations and Subpopulations for Testing Robustness in Token-Based Argument Unit Recognition. In: Proceedings of 9th Workshop on Argument Mining, 2022, 62-73.
Lentz, T. Waarom virtuele assistenten ongeïnteresseerd kunnen overkomen: De uitdaging van prosodie.Tekstblad, 28(5/6), 2022, 20.
Miaschi, A., Sarti, G., Brunato, D., Dell’Orletta, F., Venturi, G. Probing Linguistic Knowledge in Italian Neural Language Models across Language Varieties. Italian Journal of Computational Linguistics, 8(1), 2022, 25-44.
Modarressi, A., H. Mohebbi, M. T. Pilehvar. AdapLeR: Speeding up Inference by Adaptive Length Reduction. ACL 2022.
Nikolaus, M., Alishahi, A., Chrupała, G. Learning English with Peppa Pig. Transactions of the Association for Computational Linguistics, 10, 2022, 922–936.
Sarti, G., Bisazza, A., Guerberof Arenas, A., Toral, A. DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages. Proceedings EMNLP 2022, 7795-7816.
Sarti, G, Bisazza, A. InDeep × NMT: Empowering Human Translators via Interpretable Neural Machine Translation. EAMT 2022.
Shanahan, D., Burgoyne J.A. , Quinn, I. (eds.). 2022. The Oxford Handbook of Music and Corpus Studies. New York: Oxford University Press.
Sinclair, A., Jumelet, J., Zuidema, W., Fernández, R. Structural persistence in language models: Priming as a window into abstract language representations. Transactions of the Association for Computational Linguistics, 10, 2022, 1031-1050.
Vanmassenhove, E., De Sisto, M., Alhama, R. G., Lentz, T. O., Engelen, J., Shterionov, D. (2022). Preface. Computational Linguistics in the Netherlands Journal, 12, 3–5.
Vélez Vásquez, M.A., Burgoyne, J.A. Tailed U-Net: Multi-Scale Music Representation Learning. Proceedings ISMIR. 2022.
2021
Alishahi, A., Chrupała, G., Cristià, A., Dupoux, E., Higy, B., Lavechin, M., Räsänen, O., Yu, C. ZR-2021VG: Zero-Resource Speech Challenge, Visually-Grounded Language Modelling track, 2021 edition. CoRR, abs/2107.06546.
Bisazza, A, Üstün, A., Sportel, S. On the Difficulty of Translating Free-Order Case-Marking Languages. TACL, 9, (2021), pp.1233-1248.
Bosch, L. ten, Boves, L. Word Competition: An Entropy-Based Approach in the DIANA Model of Human Word Comprehension. Proceedings of Interspeech 2021, pp. 531-535.
Cornelissen, B., Zuidema, W., Burgoyne, J. A. Catafolk: Cataloguing Folk Music Datasets for Comparative Musicology. International Conference of Students of Systematic Musicology.
Cornelissen, B., Zuidema, W., Burgoyne, J.A. “Cosine Contours: A Multipurpose Representation for Melodies”, in Proceedings of the 22nd International Society for Music Information Retrieval Conference, Online, Nov 7-12, 2021.
Cornelissen, B., Zuidema, W., Burgoyne, J. A. Musical Modes as Statistical Modes: Classifying Modi in Gregorian Chant. Proceedings of the 6th International Conference on Analytical Approaches to World Music.
Hendrickx, I.H.E., Basar, M.E., Caro, L. de, Kunneman, F., Musi, E., Rapp, A. Towards a new generation of personalized intelligent conversational agents 2021, Proc. of the 29th ACM Conference on User Modeling, Adaptation and Personalization, pp. 373-374.
Higy, B., Gelderloos, L., Alishahi, A., Chrupała, G. Discrete Representations in Neural Models of Spoken Language. Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021.
Lentz, T., Nixon, J.S., Rij, J van. Temporal response modelling uncovers electrophysiological correlates of trial-by-trial error-driven learning. PsyArXiv, 14 Oct. 2021.
Reuver, M. E., Fokkens, A, Verberne, S. No NLP Task Should be an Island: Multi-disciplinarity for Diversity in News Recommender Systems. Proceedings of the EACL 2021 Hackashop on News Media Content Analysis and Automated Report Generation. Toivonen, H, Boggia, M. (eds.). Association of Computational Linguistics, pp. 45–55.
Rodd, J., Decuyper, C.H., Bosker, H.R., Bosch, L.F.M. ten. A tool for efficient and accurate segmentation of speech data. Announcing POnSS. Behavior Research Methods, 53, 2, (2021), pp. 744-756.