24.09.2024

Zahlreiche Publikationen beim EMNLP 2024 angenommen

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).