EMNLP 2024 receives 12 UKP papers
2024/09/23 by UKP Lab
We are happy to announce that 12 papers authored or co-authored by UKP members have been accepted by The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) in Miami. Congratulations to everyone involved!
The 9 main conference papers are:
»“Image, Tell me your story!” Predicting the original meta-context of visual misinformation« by Jonathan Tonglet, Marie-Francine Moens, Iryna Gurevych
»Efficient Performance Tracking: Leveraging Large Language Models for Automated Construction of Scientific Leaderboards« by Furkan Şahinuç, Thy Thy Tran, Yulia Grishina, Yufang Hou, Bei Chen, Iryna Gurevych
»Attribute or Abstain: Large Language Models as Long Document Assistants« by Jan Buchmann, Xiao Liu, Iryna Gurevych
»Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors« by Nico Daheim, Jakub Macina, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
»MixGR: Enhancing Retriever Generalization for Scientific Domain through Complementary Granularity« by Fengyu Cai, Xinran Zhao, Tong Chen, Sihao Chen, Hongming Zhang, Iryna Gurevych, Heinz Koeppl
»The Lou Dataset – Exploring the Impact of Gender-Fair Language in German Text Classification« by Andreas Waldis, Joel Birrer, Anne Lauscher, Iryna Gurevych
»Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining Datasets« by Benjamin Schiller, Johannes Daxenberger, Andreas Waldis, Iryna Gurevych
»Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs« by Haritz Puerto, Martin Tutek, Somak Aditya, Xiaodan Zhu, Iryna Gurevych
»Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document Revisions« by Qian Ruan, Ilia Kuznetsov, Iryna Gurevych
3 findings paper is:
»M2QA: Multi-domain Multilingual Question Answering« by Leon Engländer, Hannah Sterz, Clifton A Poth, Jonas Pfeiffer, Ilia Kuznetsov, Iryna Gurevych
»Scalable and Domain-General Abstractive Proposition Segmentation« by Mohammad Javad Hosseini, Yang Gao, Tim Baumgärtner, Alex Fabrikant, Reinald Kim Amplayo
»Learning from Emotions, Demographic Information and Implicit User Feedback in Task-Oriented Document-Grounded Dialogues« by Dominic Petrak, Thy Thy Tran, Iryna Gurevych