ACL

MMRefine: Unveiling the Obstacles to Robust Refinement in Multimodal Large Language Models

Gio Paik, Geewook Kim, Jinbae Im

Comments ACL Findings 2025

TaDA: Training-free recipe for Decoding with Adaptive KV Cache Compression and Mean-centering

Vinay Joshi, Pratik Prabhanjan Brahma, Zicheng Liu, Emad Barsoum

机构 * AMD 纠错

Comments ACL-2025 industry-track accepted

A MISMATCHED Benchmark for Scientific Natural Language Inference

Firoz Shaik, Mobashir Sadat, Nikita Gautam, Doina Caragea, Cornelia Caragea

机构 * Computer Science（计算机科学） ； University of Illinois Chicago（伊利诺伊大学芝加哥分校） ； Kansas State University（堪萨斯州立大学） 纠错

Comments Accepted to Findings of ACL 2025

Hierarchical-Task-Aware Multi-modal Mixture of Incremental LoRA Experts for Embodied Continual Learning

Ziqi Jia, Anmin Wang, Xiaoyang Qu, Xiaowen Yang, Jianzong Wang

机构 * Ping An Technology (Shenzhen) Co., Ltd.（平安科技（深圳）有限公司） ； Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院） ； Tsinghua University（清华大学） ； Huazhong University of Science and Technology（华中科技大学） 纠错

Comments Accepted by the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025)

Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification

Chengwu Liu, Ye Yuan, Yichun Yin, Yan Xu, Xin Xu, Zaoyu Chen, Yasheng Wang, Lifeng Shang, Qun Liu, Ming Zhang

机构 * School of Computer Science, National Key Laboratory for Multimedia Information Processing, PKU-Anker LLM Lab, Peking University（计算机学院、多媒体信息处理国家重点实验室、PKU-Anker LLM实验室、北京大学） ； Huawei Noah’s Ark Lab（华为诺亚实验室） ； The Hong Kong University of Science and Technology（香港科技大学） ； The Hong Kong Polytechnic University（香港理工大学） 纠错

Comments Accepted in ACL 2025

Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching

Jianfei Zhang, Bei Li, Jun Bai, Rumei Li, Yanmeng Wang, Chenghua Lin, Wenge Rong

机构 * School of Computer Science and Engineering, Beihang University, China（北京航空航天大学计算机科学与工程学院） ； Meituan, Inc.（美团公司） ； Beijing Institute for General Artificial Intelligence, China（北京通用人工智能研究院） ； Ping An Technology, China（平安科技） ； Department of Computer Science, University of Manchester, UK（曼彻斯特大学计算机科学系） 纠错

Comments accepted to the ACL2025 Findings

Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs

William Sheffield, Kanishka Misra, Valentina Pyatkin, Ashwini Deo, Kyle Mahowald, Junyi Jessy Li

机构 * Linguistics, The University of Texas at Austin（德克萨斯大学奥斯汀分校语言学系） ； Toyota Technological Institute at Chicago（芝加哥丰田技术研究所） ； Allen Institute for AI（人工智能研究院） ； University of Washington（华盛顿大学） 纠错

Comments To be published in Findings of The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025). The main paper is 5 pages and contains 3 figures and 1 table. In total, the paper is 12 pages and contains 8 figures and 5 tables (References + Appendix)

Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems

Emma Harvey, Emily Sheng, Su Lin Blodgett, Alexandra Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna Wallach

机构 * Cornell University（康奈尔大学） ； Microsoft Research（微软研究院） 纠错

Comments Findings of the Association for Computational Linguistics: ACL 2025

Aligning Large Language Models with Implicit Preferences from User-Generated Content

Zhaoxuan Tan, Zheng Li, Tianyi Liu, Haodong Wang, Hyokun Yun, Ming Zeng, Pei Chen, Zhihan Zhang, Yifan Gao, Ruijie Wang, Priyanka Nigam, Bing Yin, Meng Jiang

机构 * University of Notre Dame（诺特大学） ； Amazon.com Inc（亚马逊公司） 纠错

Comments Accepted to ACL 2025 Main Conference

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey

Ivan Vegner, Sydelle de Souza, Valentin Forch, Martha Lewis, Leonidas A. A. Doumas

机构 * School of Informatics, University of Edinburgh（信息学院，爱丁堡大学） ； Chemnitz University of Technology（技术大学，克明茨） ； Institute of Logic, Language, and Computation, University of Amsterdam（逻辑、语言与计算研究所，阿姆斯特丹大学） ； School of Philosophy, Psychology & Language Sciences, University of Edinburgh（哲学、心理学与语言科学学院，爱丁堡大学） 纠错

Comments To appear at ACL 2025 Main Conference

Empaths at SemEval-2025 Task 11: Retrieval-Augmented Approach to Perceived Emotions Prediction

Lev Morozov, Aleksandr Mogilevskii, Alexander Shirnin

机构 * HSE University（俄罗斯人民友谊大学） 纠错

Comments Accepted to SemEval-2025, an ACL 2025 workshop

An Efficient Task-Oriented Dialogue Policy: Evolutionary Reinforcement Learning Injected by Elite Individuals

Yangyang Zhao, Ben Niu, Libo Qin, Shihan Wang

机构 * School of Computer Science and Technology, Changsha University of Science and Technology, China（长沙理工大学计算机科学与技术学院） ； School of Computer Science and Engineering, Central South University, China（中南大学计算机科学与工程学院） ； School of Information and Computing Sciences, Utrecht University, Netherlands（乌特勒支大学信息与计算科学学院） 纠错

Comments Accepted to ACL 2025 (Main Track)

CoRe-MMRAG: Cross-Source Knowledge Reconciliation for Multimodal RAG

Yang Tian, Fan Liu, Jingyuan Zhang, Victoria W., Yupeng Hu, Liqiang Nie

Comments Accepted to ACL 2025 Main

Spectral Insights into Data-Oblivious Critical Layers in Large Language Models

Xuyuan Liu, Lei Hsiung, Yaoqing Yang, Yujun Yan

机构 * Dartmouth College（达特茅斯学院） 纠错

Comments Accepted by Findings of ACL2025

NorEval: A Norwegian Language Understanding and Generation Evaluation Benchmark

Vladislav Mikhailov, Tita Enstad, David Samuel, Hans Christian Farsethås, Andrey Kutuzov, Erik Velldal, Lilja Øvrelid

Comments Accepted for Findings of the Association for Computational Linguistics: ACL 2025

MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech Tokens

Jeong Hun Yeo, Hyeongseop Rha, Se Jin Park, Yong Man Ro

机构 * Integrated Vision and Language Lab, KAIST, South Korea（集成视觉与语言实验室，韩国科学技术院） 纠错

Comments Accepted at Findings of ACL 2025. The code and models are available https://github.com/JeongHun0716/MMS-LLaMA

Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference Alignment

Wen Yang, Junhong Wu, Chen Wang, Chengqing Zong, Jiajun Zhang

Comments Camera ready version for ACL 2025 Findings

When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Edits

Jabez Magomere, Emanuele La Malfa, Manuel Tonneau, Ashkan Kazemi, Scott Hale

Comments Accepted to ACL 2025 Findings

ATLaS: Agent Tuning via Learning Critical Steps

Zhixun Chen, Ming Li, Yuxuan Huang, Yali Du, Meng Fang, Tianyi Zhou

Comments ACL2025, Camera-ready

Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization

Keane Ong, Rui Mao, Deeksha Varshney, Erik Cambria, Gianmarco Mengaldo

机构 * National University of Singapore（新加坡国立大学） ； Nanyang Technological University（南洋理工大学） 纠错

Comments Proceedings of the Association for Computational Linguistics Main Conference (ACL 2025)

Should I Trust You? Detecting Deception in Negotiations using Counterfactual RL

Wichayaporn Wongkamjan, Yanze Wang, Feng Gu, Denis Peskoff, Jonathan K. Kummerfeld, Jonathan May, Jordan Lee Boyd-Graber

机构 * Department of Computer Science, University of Maryland（大学计算机科学系） ； Northwestern University（西北大学） ； School of Computer Science, University of Sydney（悉尼大学计算机科学学院） ； Information Sciences Institute, University of Southern California（南加州大学信息科学研究所） 纠错

Comments ACL Findings 2025

Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models

Hanin Atwany, Abdul Waheed, Rita Singh, Monojit Choudhury, Bhiksha Raj

机构 * Carnegie Mellon University（卡内基梅隆大学） ； MBZUAI（穆扎布伊人工智能研究所） 纠错

Comments ACL2025 camera-ready

On the Robust Approximation of ASR Metrics

Abdul Waheed, Hanin Atwany, Rita Singh, Bhiksha Raj

机构 * Carnegie Mellon University（卡内基梅隆大学） ； MBZUAI（穆斯林人工智能研究所） 纠错

Comments ACL 2025 camera-ready

GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice Question Answering

Cristian-George Crăciun, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel, Mihaela-Claudia Cercel

机构 * National University of Science and Technology POLITEHNICA Bucharest, Faculty of Automatic Control and Computers（波兰技术大学布加勒斯特分校国家科学与技术大学，自动控制与计算机学院） ； Technical University of Munich（慕尼黑技术大学） ； Paris 1 Panthéon-Sorbonne University（巴黎第一大学） ； University of Bucharest（布加勒斯特大学） 纠错

Comments Accepted to ACL 2025 Findings

FastDraft: How to Train Your Draft

Ofir Zafrir, Igor Margulis, Dorin Shteyman, Shira Guskin, Guy Boudoukh

机构 * Intel Labs（英特尔实验室） 纠错

Comments Accepted at ACL 2025

What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Ming Li, Yanhong Li, Tianyi Zhou

机构 * University of Maryland（马里兰大学） ； University of Chicago（芝加哥大学） 纠错

Comments ACL2025 main, Camera-ready

Self-Correction is More than Refinement: A Learning Framework for Visual and Language Reasoning Tasks

Jiayi He, Hehai Lin, Qingyun Wang, Yi Fung, Heng Ji

机构 * University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； Georgia Institute of Technology（佐治亚理工学院） ； The Hong Kong University of Science and Technology（香港科技大学） 纠错

Comments Accepted by ACL 2025 Findings

Inducing lexicons of in-group language with socio-temporal context

Christine de Kock

机构 * University of Melbourne（墨尔本大学） 纠错

Comments Accepted to ACL 2025

Leveraging LLMs for Bangla Grammar Error Correction:Error Categorization, Synthetic Data, and Model Evaluation

Pramit Bhattacharyya, Arnab Bhattacharya

Comments Accepted at ACL Findings, 2025

The Impossibility of Fair LLMs

Jacy Anthis, Kristian Lum, Michael Ekstrand, Avi Feller, Chenhao Tan

机构 * University of Chicago（芝加哥大学） ； Stanford University（斯坦福大学） ； Drexel University（德雷塞尔大学） ； University of California, Berkeley（加州大学伯克利分校） 纠错

Comments Published in ACL 2025