EMNLP

It's All About In-Context Learning! Teaching Extremely Low-Resource Languages to LLMs

Yue Li, Zhixue Zhao, Carolina Scarton

机构 * Department of Computer Science, University of Sheffield, UK（计算机科学系，谢菲尔德大学） 纠错

Comments Accepted by EMNLP 2025

ProPy: Building Interactive Prompt Pyramids upon CLIP for Partially Relevant Video Retrieval

Yi Pan, Yujia Zhang, Michael Kampffmeyer, Xiaoguang Zhao

机构 * State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（多模态人工智能系统国家重点实验室，自动化研究所，中国科学院） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（人工智能学院，中国科学院大学） ； Department of Physics and Technology, UiT The Arctic University of Norway（物理与技术系，UiT 北极大学） 纠错

Comments Accepted by EMNLP 2025 Findings

Beyond the Textual: Generating Coherent Visual Options for MCQs

Wanqiang Wang, Longzhu He, Wei Zheng

Comments EMNLP 2025

Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units

Chao Hao, Zezheng Wang, Yanhua Huang, Ruiwen Xu, Wenzhe Niu, Xin Liu, Zitong Yu

Comments Accepted by EMNLP 2025 Main Conference

BTW: A Non-Parametric Variance Stabilization Framework for Multimodal Model Integration

Jun Hou, Le Wang, Xuan Wang

机构 * Department of Computer Science, Virginia Tech, Blacksburg, VA, USA（计算机科学系，弗吉尼亚理工学院，布莱克斯堡，VA，美国） ； Department of Agricultural and Applied Economics, Virginia Tech, Blacksburg, VA, USA（农业与应用经济学系，弗吉尼亚理工学院，布莱克斯堡，VA，美国） 纠错

Journal ref The 2025 Conference on Empirical Methods in Natural Language Processing

Can Out-of-Distribution Evaluations Uncover Reliance on Shortcuts? A Case Study in Question Answering

Michal Štefánik, Timothee Mickus, Marek Kadlčík, Michal Spiegel, Josef Kuchař

机构 * Language Technology, University of Helsinki（赫尔辛基大学语言技术中心） ； Kempelen Institute of Intelligent Technologies（智能技术研究所） 纠错

Comments To appear in Findings of EMNLP 2025

Integral Transformer: Denoising Attention, Not Too Much Not Too Little

Ivan Kobyzev, Abbas Ghaddar, Dingtao Hu, Boxing Chen

机构 * Huawei Noah’s Ark Lab, Montreal Research Center, Canada（华为诺亚实验室，蒙特利尔研究中心，加拿大） 纠错

Comments EMNLP 2025 Main

Language-Specific Layer Matters: Efficient Multilingual Enhancement for Large Vision-Language Models

Yuchun Fan, Yilin Wang, Yongyu Mu, Lei Huang, Bei Li, Xiaocheng Feng, Tong Xiao, Jingbo Zhu

Comments Accepted by EMNLP 2025 findings

Can VLMs Recall Factual Associations From Visual References?

Dhananjay Ashok, Ashutosh Chaubey, Hirona J. Arai, Jonathan May, Jesse Thomason

机构 * University of Southern California（南加州大学） ； Information Sciences Institute, University of Southern California（信息科学研究所，南加州大学） 纠错

Comments To appear at EMNLP 2025 (Findings)

SDGO: Self-Discrimination-Guided Optimization for Consistent Safety in Large Language Models

Peng Ding, Wen Sun, Dailin Li, Wei Zou, Jiaming Wang, Jiajun Chen, Shujian Huang

Comments Accepted by EMNLP 2025 (Main Conference), 15 pages, 4 figures, 6 tables

Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddings

Liyan Xu, Zhenlin Su, Mo Yu, Jiangnan Li, Fandong Meng, Jie Zhou

机构 * Pattern Recognition Center, WeChat AI（微信AI模式识别中心） 纠错

Comments Accepted to EMNLP 2025 Findings

Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models

Zesen Lyu, Dandan Zhang, Wei Ye, Fangdi Li, Zhihang Jiang, Yao Yang

机构 * Hangzhou Institute for Advanced Study, UCAS（杭州高等研究 institute，UCAS） ； Zhejiang Lab（浙江实验室） ； Zhejiang University（浙江大学） 纠错

Comments Accepted by EMNLP 2025 Main conference

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models

Chen Han, Wenzhen Zheng, Xijin Tang

机构 * School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences（中国科学院大学先进交叉学科学院） ； State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences（中国科学院数学与系统科学研究院） 纠错

Comments This paper has been accepted to EMNLP 2025 (Main Conference)

SolEval: Benchmarking Large Language Models for Repository-level Solidity Code Generation

Zhiyuan Peng, Xin Yin, Rui Qian, Peiqin Lin, Yongkang Liu, Hao Zhang, Chenhao Ying, Yuan Luo

Comments Accepted By EMNLP'25-Main

Aligning NLP Models with Target Population Perspectives using PAIR: Population-Aligned Instance Replication

Stephanie Eckman, Bolei Ma, Christoph Kern, Rob Chew, Barbara Plank, Frauke Kreuter

机构 * University of Maryland, College Park（马里兰大学 College Park 分校） ； LMU Munich & Munich Center for Machine Learning（慕尼黑大学及慕尼黑机器学习中心） ； RTI International（RTI国际） 纠错

Comments EMNLP 2025 NLPerspectives Workshop

TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use

Junjie Ye, Yilong Wu, Sixian Li, Yuming Yang, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang, Peng Wang, Zhongchao Shi, Jianping Fan, Zhengyin Du

机构 * Fudan University（复旦大学） ； Lenovo Research（联想研究） ； ByteDance Seed（字节跳动种子） ； Shanghai Key Lab of Intelligent Information Processing（上海智能信息处理重点实验室） ； Shanghai AI Laboratory（上海人工智能实验室） 纠错

Comments Accepted by EMNLP 2025

Label Set Optimization via Activation Distribution Kurtosis for Zero-shot Classification with Generative Models

Yue Li, Zhixue Zhao, Carolina Scarton

机构 * Department of Computer Science, University of Sheffield, UK（计算机科学系，谢菲尔德大学） 纠错

Comments Accepted by EMNLP 2025

fLSA: Learning Semantic Structures in Document Collections Using Foundation Models

Weijia Xu, Nebojsa Jojic, Nicolas Le Roux

机构 * Microsoft Research Redmond（微软研究院雷德蒙德） 纠错

Comments EMNLP 2025 Camera Ready

Recognizing Limits: Investigating Infeasibility in Large Language Models

Wenbo Zhang, Zihang Xu, Hengrui Cai

机构 * University of California Irvine（加州大学尔滨分校） 纠错

Comments EMNLP 2025 Findings