Zahlreiche wissenschaftliche Publikationen unserer Fachrichtung wurden bei der Conference on Empirical Methods in Natural Language Processing (EMNLP) 2024 angenommen.
Herzlichen Glückwunsch an alle Autorinnen und Autoren!
- "Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations." von Matthias Lindemann, Alexander Koller und Ivan Titov.
Proceedings (EMNLP). - "Toward Compositional Behavior in Neural Models: A Survey of Current Views." von Kate McCurdy, Paul Soulos und Paul Smolensky.
Proceedings (EMNLP). - "Language models and brain alignment: beyond word-level semantics and prediction. " von Gabriele Merlin und Mariya Toneva.
- "From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP." von Marius Mosbach, Vagrant Gautam, Tomás Vergara Browne, Dietrich Klakow und Mor Geva.
Proceedings (EMNLP). - "MMAR: Multilingual and Multimodal Anaphora Resolution in Instructional Videos." von Cennet Oguz, Pascal Denis, Simon Ostermann, Emmanuel Vincent, Natalia Skachkova und Josef van Genabith.
Findings (EMNLP). - "Interpreting Translation Artifacts: A Comparative Analysis of LLMs, NMTs, and Human Translations." von Fedor Sizov, Cristina España-Bonet, Josef van Genabith, Roy Xie und Koel Dutta Chowdhury.
(WMT 2024). - "Understanding ‘Democratization’ in NLP and ML Research." von Arjun Subramonian, Vagrant Gautam, Dietrich Klakow und Zeerak Talat.
Proceedings (EMNLP). - "CoXQL: A Dataset for Parsing Explanation Requests in Conversational XAI Systems." von Qianli Wang, Tatiana Anikina, Nils Feldhus, Simon Ostermann und Sebastian Möller.
Findings (EMNLP). - "RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Framework." von Yifan Wang und Vera Demberg.
Proceedings (EMNLP). - "Scope-enhanced Compositional Semantic Parsing for DRT." von Xiulin Yang, Jonas Groschwitz, Johan Bos und Alexander Koller.
Proceedings (EMNLP). - "Predicting generalization performance with correctness discriminators." von Yuekun Yao und Alexander Koller.
Findings (EMNLP). - "Fine-Tuning Large Language Models to Translate: Will a Touch of Noisy Data in Misaligned Languages Suffice?" von Dawei Zhu, Pinzhen Chen, Miaoran Zhang, Barry Haddow, Xiaoyu Shen und Dietrich Klakow.
Proceedings (EMNLP).