EMNLP

Efficiently Editing Mixture-of-Experts Models with Compressed Experts

Yifei He, Yang Liu, Chen Liang, Hany Hassan Awadalla

机构 * University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； Microsoft（微软公司） 纠错

Comments EMNLP 2025 Findings

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation

Sashuai Zhou, Weinan Gan, Qijiong Liu, Ke Lei, Jieming Zhu, Hai Huang, Yan Xia, Ruiming Tang, Zhenhua Dong, Zhou Zhao

机构 * Zhejiang University（浙江大学） ； Huawei Noah’s Ark Lab（华为诺亚实验室） ； Shanghai AI Lab（上海人工智能实验室） ； The HK PolyU（香港理工大学） 纠错

Journal ref EMNLP 2025

Decoding the Rule Book: Extracting Hidden Moderation Criteria from Reddit Communities

Youngwoo Kim, Himanshu Beniwal, Steven L. Johnson, Thomas Hartvigsen

机构 * University of Virginia（弗吉尼亚大学） ； Indian Institute of Technology Gandhinagar（印度理工学院加尔各答） 纠错

Comments Accepted to EMNLP 2025 Main

Spotlighter: Revisiting Prompt Tuning from a Representative Mining View

Yutong Gao, Maoyuan Shao, Xinyang Huang, Chuang Zhu, Lijuan Sun, Yu Weng, Xuan Liu, Guoshun Nan

机构 * School of Information Engineering, Minzu University of China（中国民族大学信息工程学院） ； School of Artificial Intelligence, Beijing University of Posts and Telecommunications（北京邮电大学人工智能学院） ； National Library of China, Beijing, China（中国国家图书馆） ； School of Cyberspace Security, Beijing University of Posts and Telecommunications（北京邮电大学网络空间安全学院） 纠错

Comments Accepted as EMNLP 2025 Findings

Journal ref EMNLP2025

GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation

Yuanhao Ding, Esteban Garces Arias, Meimingwei Li, Julian Rodemann, Matthias Aßenmacher, Danlu Chen, Gaojuan Fan, Christian Heumann, Chongsheng Zhang

机构 * Henan University（河南大学） ； Department of Statistics, LMU Munich（慕尼黑大学统计系） ； Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心） ； CISPA Helmholtz Center for Information Security, Saarbrücken（萨尔布吕肯亥姆霍尔兹信息安全中心） ； University of California, San Diego（加州大学圣地亚哥分校） 纠错

Comments Accepted at Findings of the Association for Computational Linguistics: EMNLP 2025

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning

Wei Liu, Siya Qi, Xinyu Wang, Chen Qian, Yali Du, Yulan He

机构 * King’s College London（伦敦国王学院） ； The Alan Turing Institute（艾伦·图灵研究所） ； Shanghai Jiao Tong University（上海交通大学） 纠错

Comments 20 pages, 5 tables, 12 figures. accepted to EMNLP 2025

QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation

Mengze Hong, Wailing Ng, Chen Jason Zhang, Di Jiang

机构 * Hong Kong Polytechnic University（香港理工大学） ； AI Group, WeBank Co., Ltd（WeBank公司人工智能部） 纠错

Comments Accepted by EMNLP 2025 Main Conference. Homepage: https://github.com/mengze-hong/QualBench

Demystifying optimized prompts in language models

Rimon Melamed, Lucas H. McCabe, H. Howie Huang

机构 * The George Washington University（乔治·华盛顿大学） ； LMI Consulting（LMI咨询公司） 纠错

Comments EMNLP 2025 Main

Bias Analysis and Mitigation through Protected Attribute Detection and Regard Classification

Takuma Udagawa, Yang Zhao, Hiroshi Kanayama, Bishwaranjan Bhattacharjee

机构 * IBM Research - Tokyo（IBM东京研究实验室） ； IBM T. J. Watson Research Center（IBM T.J. Watson研究中心） 纠错

Comments Accepted to EMNLP 2025 (Findings)

Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models

Piotr Przybyła, Euan McGill, Horacio Saggion

机构 * TALN Group, Universitat Pompeu Fabra（庞培法华大学TALN小组） ； Institute of Computer Science, Polish Academy of Sciences（波兰科学院计算机科学研究所） 纠错

Comments Presented at EMNLP 2025

Learn and Unlearn: Addressing Misinformation in Multilingual LLMs

Taiming Lu, Philipp Koehn

机构 * Johns Hopkins University（约翰霍普金斯大学） 纠错

Comments EMNLP 2025 Main Conference