EMNLP

Antarlekhaka: A Comprehensive Tool for Multi-task Natural Language Annotation

Hrishikesh Terdalkar, Arnab Bhattacharya

Comments Accepted: 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS) @ EMNLP 2023

Non-autoregressive Text Editing with Copy-aware Latent Alignments

Yu Zhang, Yue Zhang, Leyang Cui, Guohong Fu

Comments EMNLP 2023

Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluation

Jinglong Gao, Xiao Ding, Bing Qin, Ting Liu

Comments Accepted to Findings of EMNLP 2023

Text-Only Training for Image Captioning using Noise-Injected CLIP

David Nukrai, Ron Mokady, Amir Globerson

Comments Will be presented at EMNLP 2022. GitHub: https://github.com/DavidHuji/CapDec

Journal ref EMNLP 2022

Compressing And Debiasing Vision-Language Pre-Trained Models for Visual Question Answering

Qingyi Si, Yuanxin Liu, Zheng Lin, Peng Fu, Weiping Wang

Comments EMNLP 2023

mGPT: Few-Shot Learners Go Multilingual

Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, Vladislav Mikhailov, Anastasia Kozlova, Tatiana Shavrina

Comments Accepted for publication at Transactions of the Association for Computational Linguistics (TACL) To be presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)

The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values

Hannah Rose Kirk, Andrew M. Bean, Bertie Vidgen, Paul Röttger, Scott A. Hale

Comments Accepted for the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP, Main)

QACHECK: A Demonstration System for Question-Guided Multi-Hop Fact-Checking

Liangming Pan, Xinyuan Lu, Min-Yen Kan, Preslav Nakov

Comments Accepted at EMNLP 2023 System Demonstrations Track

How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances

Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad, Jun Wang

Comments EMNLP 2023 main conference, paper link at https://github.com/hyintell/awesome-refreshing-llms

RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation

Yue Zhang, Leyang Cui, Enbo Zhao, Wei Bi, Shuming Shi

Comments Accepted to EMNLP 2023 (main conference, long paper)

Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators

Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong

Comments Accepted to EMNLP 2023 main conference

Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Prompting

Zhiyu Chen, Yujie Lu, William Yang Wang

Comments EMNLP 2023 Findings

NEWTON: Are Large Language Models Capable of Physical Reasoning?

Yi Ru Wang, Jiafei Duan, Dieter Fox, Siddhartha Srinivasa

Comments EMNLP 2023 Findings; 8 pages, 3 figures, 7 tables; Project page: https://newtonreasoning.github.io

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi

Comments 25 pages; 7 figures. Published as a main conference paper at EMNLP 2023. Code available at https://github.com/shmsw25/FActScore

Knowledge Rumination for Pre-trained Language Models

Yunzhi Yao, Peng Wang, Shengyu Mao, Chuanqi Tan, Fei Huang, Huajun Chen, Ningyu Zhang

Comments EMNLP 2023

Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks

Xianzhi Li, Samuel Chan, Xiaodan Zhu, Yulong Pei, Zhiqiang Ma, Xiaomo Liu, Sameena Shah

Comments Add more experiments, accepted to EMNLP 2023 Industry track

An Empirical Study of Multimodal Model Merging

Yi-Lin Sung, Linjie Li, Kevin Lin, Zhe Gan, Mohit Bansal, Lijuan Wang

Comments EMNLP 2023 Findings

SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Potsawee Manakul, Adian Liusie, Mark J. F. Gales

Comments EMNLP 2023 (main conference)

Query2doc: Query Expansion with Large Language Models

Liang Wang, Nan Yang, Furu Wei

Comments Accepted to EMNLP 2023

Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency

Eric Zelikman, Wanjing Anya Ma, Jasmine E. Tran, Diyi Yang, Jason D. Yeatman, Nick Haber

Comments Accepted to EMNLP 2023 (Main)

Text Embeddings Reveal (Almost) As Much As Text

John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush

Comments Accepted at EMNLP 2023

Topic-DPR: Topic-based Prompts for Dense Passage Retrieval

Qingfa Xiao, Shuangyin Li, Lei Chen

Comments Findings of EMNLP 2023

Rationale-Enhanced Language Models are Better Continual Relation Learners

Weimin Xiong, Yifan Song, Peiyi Wang, Sujian Li

Comments Accepted at EMNLP 2023

A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News Articles

Daria-Mihaela Broscoteanu, Radu Tudor Ionescu

Comments Accepted at EMNLP 2023

P5: Plug-and-Play Persona Prompting for Personalized Response Selection

Joosung Lee, Minsik Oh, Donghun Lee

Comments EMNLP 2023 main conference

InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective

Yifan Song, Peiyi Wang, Weimin Xiong, Dawei Zhu, Tianyu Liu, Zhifang Sui, Sujian Li

Comments Findings of EMNLP 2023. An improved version of arXiv:2305.07289

Selective Demonstrations for Cross-domain Text-to-SQL

Shuaichen Chang, Eric Fosler-Lussier

Comments EMNLP 2023

Towards Mitigating Hallucination in Large Language Models via Self-Reflection

Ziwei Ji, Tiezheng Yu, Yan Xu, Nayeon Lee, Etsuko Ishii, Pascale Fung

Comments Accepted by the findings of EMNLP 2023

Compressing Context to Enhance Inference Efficiency of Large Language Models

Yucheng Li, Bo Dong, Chenghua Lin, Frank Guerin

Comments EMNLP 2023. arXiv admin note: substantial text overlap with arXiv:2304.12102; text overlap with arXiv:2303.11076 by other authors

BYOC: Personalized Few-Shot Classification with Co-Authored Class Descriptions

Arth Bohra, Govert Verkes, Artem Harutyunyan, Pascal Weinberger, Giovanni Campagna

Comments Accepted at EMNLP 2023 (Findings)