EMNLP

COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier

Gaoxiang Luo, Aryan Deshwal

机构 * University of Minnesota（明尼苏达大学） 纠错

Comments Accepted by EMNLP 2025 Main, Code: https://github.com/GaoxiangLuo/COM-BOM

GRAD: Generative Retrieval-Aligned Demonstration Sampler for Efficient Few-Shot Reasoning

Oussama Gabouj, Kamel Charaf, Ivan Zakazov, Nicolas Baldwin, Robert West

机构 * EPFL（苏黎世联邦理工学院） 纠错

Comments EMNLP 2025 (findings)

Unpacking Let Alone: Human-Scale Models Generalize to a Rare Construction in Form but not Meaning

Wesley Scivetti, Tatsuya Aoyama, Ethan Wilcox, Nathan Schneider

机构 * Georgetown University（杰克逊维尔大学） 纠错

Comments Empirical Methods for Natural Language Processing (EMNLP) 2025, Camera-Ready Version

GuRE:Generative Query REwriter for Legal Passage Retrieval

Daehee Kim, Deokhyung Kang, Jonghwi Kim, Sangwon Ryu, Gary Geunbae Lee

机构 * Graduate School of Artificial Intelligence, POSTECH, Republic of Korea（人工智能研究生院，POSTECH，大韩民国） ； AI Future Lab, KT, Republic of Korea（AI未来实验室，KT，大韩民国） ； Department of Computer Science and Engineering, POSTECH, Republic of Korea（计算机科学与工程系，POSTECH，大韩民国） 纠错

Comments NLLP Workshop at EMNLP 2025

Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks

Eileen Pan, Anna Seo Gyeong Choi, Maartje ter Hoeve, Skyler Seto, Allison Koenecke

机构 * Department of Information Science, Cornell University（康奈尔大学信息科学系） ； Apple（苹果公司） ； Cornell Tech（康奈尔科技） 纠错

Comments EMNLP Findings 2025, 12 pages, 11 tables, 3 figures

What You See is What You Ask: Evaluating Audio Descriptions

Divy Kala, Eshika Khandelwal, Makarand Tapaswi

机构 * CVIT, IIIT Hyderabad（计算机视觉与人工智能技术研究所，IIIT海得拉巴） 纠错

Comments EMNLP 2025 Main Track Long Paper

Facilitating Cognitive Accessibility with LLMs: A Multi-Task Approach to Easy-to-Read Text Generation

François Ledoyen, Gaël Dias, Jeremie Pantin, Alexis Lechervy, Fabrice Maurel, Youssef Chahir

机构 * Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ, GREYC UMR 6072（法国卡恩大学、ENSICAEN、CNRS、诺曼底大学、GREYC UMR 6072） ； Koena SAS 纠错

Comments EMNLP 2025

Are Large Language Models Chronically Online Surfers? A Dataset for Chinese Internet Meme Explanation

Yubo Xie, Chenkai Wang, Zongyang Ma, Fahui Miao

机构 * Shanghai Maritime University（上海 Maritime 大学） ； École Polytechnique Fédérale de Lausanne（瑞士联邦理工学院） ； Xi’an Jiaotong Liverpool University（西安交通大学利物浦大学） 纠错

Comments Accepted to EMNLP 2025 Main Conference. 22 pages, 3 figures, 13 tables. GitHub: github.com/yuboxie/chime

Spectral Scaling Laws in Language Models: How Effectively Do Feed-Forward Networks Use Their Latent Space?

Nandan Kumar Jha, Brandon Reagen

机构 * New York University（纽约大学） 纠错

Comments EMNLP 2025 Main Conference (Long paper)

Enhancing Rating Prediction with Off-the-Shelf LLMs Using In-Context User Reviews

Koki Ryu, Hitomi Yanaka

机构 * The University of Tokyo（东京大学） ； Riken（理化学研究所） 纠错

Comments Accepted to EMNLP 2025 PALS Workshop

Efficient Layer-wise LLM Fine-tuning for Revision Intention Prediction

Zhexiong Liu, Diane Litman

机构 * Department of Computer Science, Learning Research & Development Center University of Pittsburgh（计算机科学系、学习研究与开发中心匹兹堡大学） 纠错

Comments In The Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2025

PrimeX: A Dataset of Worldview, Opinion, and Explanation

Rik Koncel-Kedziorski, Brihi Joshi, Tim Paek

机构 * Apple（苹果公司） ； University of Southern California（南加州大学） 纠错

Comments EMNLP 2025 Main

Explaining novel senses using definition generation with open language models

Mariia Fedorova, Andrey Kutuzov, Francesco Periti, Yves Scherrer

机构 * University of Oslo（奥斯陆大学） ； KU Leuven - Flanders Make（库尔勒文大学-佛兰德斯制造） 纠错

Comments EMNLP 2025 Findings

Taxonomy of Comprehensive Safety for Clinical Agents

Jean Seo, Hyunkyung Lee, Gibaeg Kim, Wooseok Han, Jaehyo Yoo, Seungseop Lim, Kihun Shin, Eunho Yang

Comments EMNLP 2025 Industry

Out of the Box, into the Clinic? Evaluating State-of-the-Art ASR for Clinical Applications for Older Adults

Bram van Dijk, Tiberon Kuiper, Sirin Aoulad si Ahmed, Armel Levebvre, Jake Johnson, Jan Duin, Simon Mooijaart, Marco Spruit

机构 * Department of Public Health and Primary Care, Leiden University Medical Center（莱顿大学医学中心公共卫生与初级保健系） ； Leiden Institute of Advanced Computer Science, Leiden University（莱顿大学高级计算机科学研究所） ； Center for Medicine for Older People, Leiden University Medical Center（莱顿大学医学中心老年医学中心） ； Department of Internal Medicine, Leiden University Medical Center（莱顿大学医学中心内科系） 纠错

Comments Forthcoming in the Proceedings of the Fourth Workshop on Bridging Human Computer Interaction and Natural Language Processing HCINLP (EMNLP)

What if Othello-Playing Language Models Could See?

Xinyi Chen, Yifei Yuan, Jiaang Li, Serge Belongie, Maarten de Rijke, Anders Søgaard

机构 * University of Amsterdam（阿姆斯特丹大学） ； ETH Zürich（苏黎世联邦理工学院） ； University of Copenhagen（哥本哈根大学） 纠错

Comments ICML 2025 Assessing World Models Workshop; EMNLP 2025 Findings

Are Knowledge and Reference in Multilingual Language Models Cross-Lingually Consistent?

Xi Ai, Mahardika Krisna Ihsani, Min-Yen Kan

Comments EMNLP'25 Findings Camera Ready

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers

Tommaso Green, Martin Gubri, Haritz Puerto, Sangdoo Yun, Seong Joon Oh

机构 * Parameter Lab（参数实验室） ； Data and Web Science Group（数据与网络科学小组） ； University of Mannheim（曼海姆大学） ； UKP Lab（UKP实验室） ； Technical University of Darmstadt（达姆施塔特技术大学） ； NAVER AI Lab（NAVER人工智能实验室） ； University of Tübingen（图宾根大学） ； Tübingen AI Center（图宾根人工智能中心） 纠错

Comments Accepted to EMNLP 2025 (Main)

Steering LLM Reasoning Through Bias-Only Adaptation

Viacheslav Sinii, Alexey Gorbatovski, Artem Cherepanov, Boris Shaposhnikov, Nikita Balagansky, Daniil Gavrilov

机构 * T-Tech ； Central University（中央大学） 纠错

Comments EMNLP 2025

Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing

Bhiman Kumar Baghel, Emma Jordan, Zheyuan Ryan Shi, Xiang Lorraine Li

机构 * Department of Computer Science, University of Pittsburgh, PA, USA（计算机科学系，匹兹堡大学，宾夕法尼亚州，美国） 纠错

Comments Accepted at EMNLP 2025 as Findings

Exploring and Controlling Diversity in LLM-Agent Conversation

KuanChao Chu, Yi-Pei Chen, Hideki Nakayama

机构 * The University of Tokyo（东京大学） 纠错

Comments EMNLP 2025 Findings