EMNLP

PEDANTS: Cheap but Effective and Interpretable Answer Equivalence

Zongxia Li, Ishani Mondal, Yijun Liang, Huy Nghiem, Jordan Lee Boyd-Graber

Comments Efficient PEDANTS Classifier for short-form QA in github: https://github.com/zli12321/qa_metrics. arXiv admin note: text overlap with arXiv:2401.13170

Journal ref Empirical Methods in Natural Language Processing 2024

Conditional and Modal Reasoning in Large Language Models

Wesley H. Holliday, Matthew Mandelkern, Cedegao E. Zhang

Comments Accepted for The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024). Final version includes additional models and additional inference patterns

How Far Can We Extract Diverse Perspectives from Large Language Models?

Shirley Anugrah Hayati, Minhwa Lee, Dheeraj Rajagopal, Dongyeop Kang

Comments Accepted at EMNLP 2024 Main Conference

Decoding Susceptibility: Modeling Misbelief to Misinformation Through a Computational Approach

Yanchen Liu, Mingyu Derek Ma, Wenna Qin, Azure Zhou, Jiaao Chen, Weiyan Shi, Wei Wang, Diyi Yang

Comments EMNLP 2024

LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay

Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, Hao Wang

Comments Accepted by EMNLP 2024

Mitigating the Alignment Tax of RLHF

Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang

Comments EMNLP 2024 Main

Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction

Menglin Xia, Xuchao Zhang, Camille Couturier, Guoqing Zheng, Saravan Rajmohan, Victor Ruhle

Comments Accepted at EMNLP 2024 Industry Track

Improved Compositional Generalization by Generating Demonstrations for Meta-Learning

Sam Spilsbury, Pekka Marttinen, Alexander Ilin

Comments EMNLP 2024

MiRAGeNews: Multimodal Realistic AI-Generated News Detection

Runsheng Huang, Liam Dugan, Yue Yang, Chris Callison-Burch

Comments EMNLP 2024 Findings

Mentor-KD: Making Small Language Models Better Multi-step Reasoners

Hojae Lee, Junho Kim, SangKeun Lee

Comments EMNLP 2024

ALVIN: Active Learning Via INterpolation

Michalis Korakakis, Andreas Vlachos, Adrian Weller

Comments Accepted to EMNLP 2024 (Main)

Wikimedia data for AI: a review of Wikimedia datasets for NLP tasks and AI-assisted editing

Isaac Johnson, Lucie-Aimée Kaffee, Miriam Redi

Comments Accepted to NLP for Wikipedia Workshop at EMNLP '24

Lifelong Event Detection via Optimal Transport

Viet Dao, Van-Cuong Pham, Quyen Tran, Thanh-Thien Le, Linh Ngo Van, Thien Huu Nguyen

Comments Accepted to EMNLP 2024

Measuring the Groundedness of Legal Question-Answering Systems

Dietrich Trautmann, Natalia Ostapuk, Quentin Grail, Adrian Alan Pol, Guglielmo Bonifazi, Shang Gao, Martin Gajek

Comments to appear NLLP @ EMNLP 2024

Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models

Yeeun Kim, Young Rok Choi, Eunkyung Choi, Jinhwan Choi, Hai Jin Park, Wonseok Hwang

Comments EMNLP 2024 Findings

QEFT: Quantization for Efficient Fine-Tuning of LLMs

Changhun Lee, Jun-gyu Jin, Younghyun Cho, Eunhyeok Park

Comments Accepted at Findings of EMNLP 2024

Retrieving Contextual Information for Long-Form Question Answering using Weak Supervision

Philipp Christmann, Svitlana Vakulenko, Ionut Teodor Sorodoc, Bill Byrne, Adrià de Gispert

Comments Accepted at EMNLP 2024 (Findings)

From the Least to the Most: Building a Plug-and-Play Visual Reasoner via Data Synthesis

Chuanqi Cheng, Jian Guan, Wei Wu, Rui Yan

Comments Accepted by EMNLP 2024

PostMark: A Robust Blackbox Watermark for Large Language Models

Yapei Chang, Kalpesh Krishna, Amir Houmansadr, John Wieting, Mohit Iyyer

Comments EMNLP 2024; 19 pages, 5 figures

Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving

Xin Quan, Marco Valentino, Louise A. Dennis, André Freitas

Comments Camera-ready for EMNLP 2024

Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment

Yiju Guo, Ganqu Cui, Lifan Yuan, Ning Ding, Zexu Sun, Bowen Sun, Huimin Chen, Ruobing Xie, Jie Zhou, Yankai Lin, Zhiyuan Liu, Maosong Sun

Comments EMNLP 2024 main conference

Generation with Dynamic Vocabulary

Yanting Liu, Tao Ji, Changzhi Sun, Yuanbin Wu, Xiaoling Wang

Comments EMNLP 2024

Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains

Krithika Ramesh, Nupoor Gandhi, Pulkit Madaan, Lisa Bauer, Charith Peris, Anjalie Field

Comments Accepted to EMNLP 2024 (Findings)

DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models

Yiming Huang, Jianwen Luo, Yan Yu, Yitong Zhang, Fangyu Lei, Yifan Wei, Shizhu He, Lifu Huang, Xiao Liu, Jun Zhao, Kang Liu

Comments EMNLP 2024

Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasets

Melanie Walsh, Anna Preus, Maria Antoniak

Comments 2024 EMNLP Findings

Not All Preference Pairs Are Created Equal: A Recipe for Annotation-Efficient Iterative Preference Learning

Sen Yang, Leyang Cui, Deng Cai, Xinting Huang, Shuming Shi, Wai Lam

Comments Findings of EMNLP 2024

Can LLM Graph Reasoning Generalize beyond Pattern Memorization?

Yizhuo Zhang, Heng Wang, Shangbin Feng, Zhaoxuan Tan, Xiaochuang Han, Tianxing He, Yulia Tsvetkov

Comments 17 pages, 6 figures. EMNLP 2024 Findings. Code and data is publicly available at https://github.com/MatthewYZhang/NLGift

Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration

Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, Yulia Tsvetkov

Comments EMNLP 2024

Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization

Sungbin Shin, Wonpyo Park, Jaeho Lee, Namhoon Lee

Comments EMNLP 2024 main

Consecutive Batch Model Editing with HooK Layers

Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam

Comments To appear in EMNLP 2024 Main