EMNLP

Masked Diffusion Captioning for Visual Feature Learning

Chao Feng, Zihao Wei, Andrew Owens

机构 * University of Michigan（密歇根大学） ； Cornell University（康奈尔大学） ； University of Maryland（马里兰大学） 纠错

Comments EMNLP 2025 (Findings). Project page: https://cfeng16.github.io/mdlm4vfl/

Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality

Yuto Harada, Yusuke Yamauchi, Yusuke Oda, Yohei Oseki, Yusuke Miyao, Yu Takagi

机构 * NII LLMC（日本信息处理学会大语言模型中心） ； The University of Tokyo（东京大学） ； NAIST（日本科学技术大学） ； Nagoya Institute of Technology（名古屋技术大学） 纠错

Comments Accepted to EMNLP 2025 (Main Conference). Models and evaluation results available at: https://github.com/llm-jp/massive-sft

Comparing human and LLM politeness strategies in free production

Haoran Zhao, Robert D. Hawkins

机构 * Department of Linguistics University of Washington（语言学系华盛顿大学） ； Department of Linguistics Stanford University（语言学系斯坦福大学） 纠错

Comments 25 pages, 5 figures | EMNLP 2025 camera-ready version

1+1>2: A Synergistic Sparse and Low-Rank Compression Method for Large Language Models

Zeliang Zong, Kai Zhang, Zheyang Li, Wenming Tan, Ye Ren, Yiyan Zhai, Jilin Hu

机构 * Hikvision Research Institute（海康威视研究院） ； School of Data Science and Engineering, East China Normal University（华东师范大学数据科学与工程学院） 纠错

Comments 15 pages, 6 figures, EMNLP 2025 findings

RCScore: Quantifying Response Consistency in Large Language Models

Dongjun Jang, Youngchae Ahn, Hyopil Shin

Journal ref EMNLP 2025 Main Conference

Bridging the Gap Between Molecule and Textual Descriptions via Substructure-aware Alignment

Hyuntae Park, Yeachan Kim, SangKeun Lee

Comments EMNLP 2025 (main)

CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments

Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou, Beatriz Borges, Irina Rish, Antoine Bosselut

机构 * EPFL（瑞士联邦理工学院） ； MILA（蒙特利尔人工智能研究院） 纠错

Journal ref 2025 Conference on Empirical Methods in Natural Language Processing

Evaluating the Role of Verifiers in Test-Time Scaling for Legal Reasoning Tasks

Davide Romano, Jonathan Schwarz, Daniele Giofré

机构 * Thomson Reuters（汤姆森·路透） 纠错

Comments Accepted to EMNLP - NLLP Workshop

VC4VG: Optimizing Video Captions for Text-to-Video Generation

Yang Du, Zhuoran Lin, Kaiqiang Song, Biao Wang, Zhicheng Zheng, Tiezheng Ge, Bo Zheng, Qin Jin

机构 * School of Information, Renmin University of China（中国人民大学信息学院） ； Taobao & Tmall Group of Alibaba（阿里巴巴淘宝与天猫集团） 纠错

Comments Accepted by EMNLP 2025

TRUST-VL: An Explainable News Assistant for General Multimodal Misinformation Detection

Zehong Yan, Peng Qi, Wynne Hsu, Mong Li Lee

Comments EMNLP 2025 Oral; Project Homepage: https://yanzehong.github.io/trust-vl/

Large Language Models Have Intrinsic Meta-Cognition, but Need a Good Lens

Ziyang Ma, Qingyue Yuan, Zhenglin Wang, Deyu Zhou

机构 * School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, China（计算机科学与工程学院、计算机网络与信息集成重点实验室、教育部、东南大学，中国） ； Department of Neurosurgery, Shanghai Tenth People’s Hospital, School of Clinical Medicine of Nanjing Medical University, China（神经外科科、上海第十人民医院、南京医科大学临床医学学院，中国） 纠错

Comments Accepted to EMNLP 2025

Unstructured Evidence Attribution for Long Context Query Focused Summarization

Dustin Wright, Zain Muhammad Mujahid, Lu Wang, Isabelle Augenstein, David Jurgens

机构 * Department of Computer Science, University of Copenhagen（哥本哈根大学计算机科学系） ； Department of Computer Science and Engineering, University of Michigan（密歇根大学计算机科学与工程系） ； School of Information, University of Michigan（密歇根大学信息学院） 纠错

Comments EMNLP 2025 Main; 29 pages; 24 figures; 8 tables