EMNLP

Recent Trends in Linear Text Segmentation: a Survey

Iacopo Ghinassi, Lin Wang, Chris Newell, Matthew Purver

Journal ref Findings of the Association for Computational Linguistics: EMNLP 2024

When Babies Teach Babies: Can student knowledge sharing outperform Teacher-Guided Distillation on small datasets?

Srikrishna Iyer

Comments Accepted to BabyLM challenge, CoNLL Workshop, EMNLP 2024

Towards Robust Evaluation of Unlearning in LLMs via Data Transformations

Abhinav Joshi, Shaswati Saha, Divyaksh Shukla, Sriram Vema, Harsh Jhamtani, Manas Gaur, Ashutosh Modi

Comments Accepted at EMNLP 2024 Findings; 21 pages (5 page main content + references + appendix)

The GPT-WritingPrompts Dataset: A Comparative Analysis of Character Portrayal in Short Stories

Xi Yu Huang, Krishnapriya Vishnubhotla, Frank Rudzicz

Comments 9 pages plus appendices; published at the 6th Workshop on Narrative Understanding, EMNLP 2024

Emotion Granularity from Text: An Aggregate-Level Indicator of Mental Health

Krishnapriya Vishnubhotla, Daniela Teodorescu, Mallory J. Feldman, Kristen A. Lindquist, Saif M. Mohammad

Comments 9 pages plus appendices; published as a long paper at EMNLP 2024

Enhancing Post-Hoc Attributions in Long Document Comprehension via Coarse Grained Answer Decomposition

Pritika Ramu, Koustava Goswami, Apoorv Saxena, Balaji Vasan Srinivasan

Comments EMNLP 2024

A Study of Nationality Bias in Names and Perplexity using Off-the-Shelf Affect-related Tweet Classifiers

Valentin Barriere, Sebastian Cifuentes

Comments updated EMNLP camera ready version

Journal ref (2024), Proceedings of EMNLP, 569-579

Is This a Bad Table? A Closer Look at the Evaluation of Table Generation from Text

Pritika Ramu, Aparna Garimella, Sambaran Bandyopadhyay

Comments EMNLP 2024 (short)

Provenance: A Light-weight Fact-checker for Retrieval Augmented LLM Generation Output

Hithesh Sankararaman, Mohammed Nasheed Yasin, Tanner Sorensen, Alessandro Di Bari, Andreas Stolcke

Comments To appear in Proceedings of EMNLP 2024 Industry Track

Journal ref Proc. 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track, pp. 1305-1313

Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling

Daehoon Gwak, Junwoo Park, Minho Park, Chaehun Park, Hyunchan Lee, Edward Choi, Jaegul Choo

Comments EMNLP 2024 Findings

BERTrend: Neural Topic Modeling for Emerging Trends Detection

Allaa Boutaleb, Jerome Picault, Guillaume Grosjean

Comments 17 pages, 12 figures, FuturED 2024: Workshop on Future of Event Detection (CoLocated with EMNLP 2024)

RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine

Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho, Haeyu Jeong, Jungmin Kong, Saehun Kim, Keunchan Park, Sarah Cho, Inchang Jeong, Gyohee Nam, Sunghoon Han, Wonil Yang, Jaeho Choi

Comments Accepted to EMNLP 2024 Industry Track. First two authors contributed equally

When Context Leads but Parametric Memory Follows in Large Language Models

Yufei Tao, Adam Hiatt, Erik Haake, Antonie J. Jetter, Ameeta Agrawal

Comments Accepted by EMNLP 2024 Main Conference

Word Alignment as Preference for Machine Translation

Qiyu Wu, Masaaki Nagata, Zhongtao Miao, Yoshimasa Tsuruoka

Comments EMNLP 2024 Main

REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering

Yuhao Wang, Ruiyang Ren, Junyi Li, Wayne Xin Zhao, Jing Liu, Ji-Rong Wen

Comments Accepted to EMNLP 2024 Main Conference. Published on ACL Anthology: https://aclanthology.org/2024.emnlp-main.321.pdf

Schema-Driven Information Extraction from Heterogeneous Tables

Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, Alan Ritter

Comments Accepted to EMNLP 2024 Findings

Fine-Grained Detection of Solidarity for Women and Migrants in 155 Years of German Parliamentary Debates

Aida Kostikova, Benjamin Paassen, Dominik Beese, Ole Pütz, Gregor Wiedemann, Steffen Eger

Comments EMNLP 2024 (Main Conference) Camera-Ready Version

Probing the Capacity of Language Model Agents to Operationalize Disparate Experiential Context Despite Distraction

Sonny George, Chris Sypherd, Dylan Cashman

Journal ref Findings Assoc. Comput. Linguistics: EMNLP 2024 15447-15459 (2024)

Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?

Daniel P. Jeong, Saurabh Garg, Zachary C. Lipton, Michael Oberst

Comments This version was published at EMNLP 2024 Main Conference as a Long Paper (Oral). See the extended version (arXiv:2411.08870) for additional results on QA tasks based on clinical notes and evaluations in the supervised fine-tuning regime

BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?

Zongmeng Zhang, Jinhua Zhu, Wengang Zhou, Xiang Qi, Peng Zhang, Houqiang Li

Comments Findings of the Association for Computational Linguistics: EMNLP 2024

Journal ref In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 2767-2779

Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction

Sergio Burdisso, Srikanth Madikeri, Petr Motlicek

Comments Accepted to EMNLP 2024 main conference

Journal ref https://aclanthology.org/2024.emnlp-main.310/

Enhancing Training Data Attribution for Large Language Models with Fitting Error Consideration

Kangxi Wu, Liang Pang, Huawei Shen, Xueqi Cheng

Comments Accepted to the EMNLP 2024 main

Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification

Ming Li, Jike Zhong, Chenxin Li, Liuzhuozheng Li, Nie Lin, Masashi Sugiyama

Comments EMNLP 2024 Main Conference

Divide-or-Conquer? Which Part Should You Distill Your LLM?

Zhuofeng Wu, He Bai, Aonan Zhang, Jiatao Gu, VG Vinod Vydiswaran, Navdeep Jaitly, Yizhe Zhang

Comments Findings of the Association for Computational Linguistics: EMNLP 2024

Journal ref 2024.findings-emnlp.145

Re-Reading Improves Reasoning in Large Language Models

Xiaohan Xu, Chongyang Tao, Tao Shen, Can Xu, Hongbo Xu, Guodong Long, Jian-guang Lou, Shuai Ma

Comments EMNLP 2024 Main

Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted Narratives

Xinliang Frederick Zhang, Nick Beauchamp, Lu Wang

Comments EMNLP'24 Findings

Enhancing High-order Interaction Awareness in LLM-based Recommender Model

Xinfeng Wang, Jin Cui, Fumiyo Fukumoto, Yoshimi Suzuki

Comments Long paper accepted to EMNLP 2024 Main. 16 pages

OpenOmni: A Collaborative Open Source Tool for Building Future-Ready Multimodal Conversational Agents

Qiang Sun, Yuanyi Luo, Sirui Li, Wenxiao Zhang, Wei Liu

Comments Published in Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP 2024) Best Demo Paper Award at EMNLP 2024

Journal ref EMNLP 2024 (System Demonstrations), pp. 46-52

Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns?

Kuei-Chun Kao, Ruochen Wang, Cho-Jui Hsieh

Journal ref https://aclanthology.org/2024.findings-emnlp.980/

ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees

Zhiyuan Wang, Jinhao Duan, Lu Cheng, Yue Zhang, Qingni Wang, Xiaoshuang Shi, Kaidi Xu, Hengtao Shen, Xiaofeng Zhu

Comments Accepted by EMNLP 2024 Findings