EMNLP

STARE at the Structure: Steering ICL Exemplar Selection with Structural Alignment

Jiaqian Li, Qisheng Hu, Jing Li, Wenya Wang

机构 * Nanyang Technological University, Singapore（南洋理工大学） ； Harbin Institute of Technology, Shenzhen, China（哈尔滨工业大学（深圳）） 纠错

Comments EMNLP 2025 Main

GDLLM: A Global Distance-aware Modeling Approach Based on Large Language Models for Event Temporal Relation Extraction

Jie Zhao, Wanting Ning, Yuxiao Fei, Yubo Feng, Lishuang Li

机构 * School of Computer Science and Technology, Dalian University of Technology, China（大连理工大学计算机科学与技术学院） ； Luddy School of Informatics, Computing, and Engineering, Indiana University Indianapolis, the United States（印第安纳大学印第安纳波利斯分校信息学院） 纠错

Comments Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP Findings)

Leveraging Semantic Triples for Private Document Generation with Local Differential Privacy Guarantees

Stephen Meisenbacher, Maulik Chevli, Florian Matthes

机构 * Technical University of Munich School of Computation, Information and Technology Department of Computer Science（慕尼黑技术大学计算、信息与技术学院计算机科学系） 纠错

Comments 17 pages, 2 figures, 11 tables. Accepted to EMNLP 2025 (Main)

Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark

Chihiro Taguchi, Seng Mai, Keita Kurabe, Yusuke Sakai, Georgina Agyei, Soudabeh Eslami, David Chiang

机构 * University of Notre Dame（诺特达姆大学） ； University of Washington（华盛顿大学） ； Tokyo University of Foreign Studies（东京外国语大学） ； Nara Institute of Science and Technology（奈良科学技術大学） ； University of Tübingen（图宾根大学） 纠错

Comments 13 pages, 7 tables, 2 figures. Accepted at EMNLP Main 2025. Code and data released at https://github.com/ctaguchi/LSLB

Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning

Yicong Wu, Guangyue Lu, Yuan Zuo, Huarong Zhang, Junjie Wu

Comments Accepted at EMNLP 2025

SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning

Yicheng Ji, Jun Zhang, Heming Xia, Jinpeng Chen, Lidan Shou, Gang Chen, Huan Li

机构 * The State Key Laboratory of Blockchain and Data Security（区块链与数据安全国家重点实验室） ； Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security（杭州高新技术区（滨江）区块链与数据安全研究院） ； Department of Computing, The Hong Kong Polytechnic University（香港理工大学计算机系） ； School of Computer Science, Beijing University of Posts and Telecommunications（北京邮电大学计算机学院） 纠错

Comments Accepted at EMNLP 2025 Main

GLProtein: Global-and-Local Structure Aware Protein Representation Learning

Yunqing Liu, Wenqi Fan, Xiaoyong Wei, Qing Li

机构 * Department of Computing (COMP), The Hong Kong Polytechnic University（计算机学院（COMP），香港理工大学） ； Department of Management and Marketing (MM), The Hong Kong Polytechnic University（管理与营销学院（MM），香港理工大学） ； Department of Computer Science, Sichuan University（计算机学院，四川大学） 纠错

Comments Accepted to EMNLP 2025 Findings

CoMoE: Contrastive Representation for Mixture-of-Experts in Parameter-Efficient Fine-tuning

Jinyuan Feng, Chaopeng Wei, Tenghai Qiu, Tianyi Hu, Zhiqiang Pu

机构 * Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； University of Science and Technology Beijing（北京科技大学） 纠错

Comments Accepted by EMNLP Findings 2025

Joint Enhancement of Relational Reasoning for Long-Context LLMs

Zhirui Chen, Wei Shen, Jiashui Huang, Ling Shao

机构 * UCAS-Terminus AI Lab, University of Chinese Academy of Sciences, China（中国科学院大学Terminus AI实验室，中国科学院大学） 纠错

Comments 9 pages, 5 pages Accepted by EMNLP 2025 Findings

Seeing is Believing: Emotion-Aware Audio-Visual Language Modeling for Expressive Speech Generation

Weiting Tan, Jiachen Lian, Hirofumi Inaguma, Paden Tomasello, Philipp Koehn, Xutai Ma

机构 * Johns Hopkins University（约翰霍普金斯大学） ； Meta AI Research（Meta AI 研究） 纠错

Comments EMNLP 2025 (Findings)

Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging

Hua Farn, Hsuan Su, Shachi H Kumar, Saurav Sahay, Shang-Tse Chen, Hung-yi Lee

机构 * National Taiwan University（国立台湾大学） ； Intel Lab（英特尔实验室） 纠错

Comments EMNLP 2025 Findings