EMNLP

ParroT: Translating during Chat using Large Language Models tuned with Human Translation and Feedback

Wenxiang Jiao, Jen-tse Huang, Wenxuan Wang, Zhiwei He, Tian Liang, Xing Wang, Shuming Shi, Zhaopeng Tu

Comments 12 pages; EMNLP 2023 (Findings)

DeltaScore: Fine-Grained Story Evaluation with Perturbations

Zhuohan Xie, Miao Li, Trevor Cohn, Jey Han Lau

Comments 15 pages, 3 figures, 8 tables. Camera ready version for EMNLP 2023 findings

End-to-End Single-Channel Speaker-Turn Aware Conversational Speech Translation

Juan Zuluaga-Gomez, Zhaocheng Huang, Xing Niu, Rohit Paturi, Sundararajan Srinivasan, Prashant Mathur, Brian Thompson, Marcello Federico

Comments Accepted at EMNLP 2023. Code: https://github.com/amazon-science/stac-speech-translation

Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs

Xue-Yong Fu, Md Tahmid Rahman Laskar, Cheng Chen, Shashi Bhushan TN

Comments accepted by Generation, Evaluation & Metrics (GEM) Workshop at EMNLP 2023

Text Rendering Strategies for Pixel Language Models

Jonas F. Lotz, Elizabeth Salesky, Phillip Rust, Desmond Elliott

Comments EMNLP 2023

Robustness Tests for Automatic Machine Translation Metrics with Adversarial Attacks

Yichen Huang, Timothy Baldwin

Comments Accepted in Findings of EMNLP 2023

AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification

Yongxin Huang, Kexin Wang, Sourav Dutta, Raj Nath Patel, Goran Glavaš, Iryna Gurevych

Comments Accepted at EMNLP 2023 Main

Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition

Chenxu Wang, Ping Jian, Mu Huang

Comments This paper is accepted by the EMNLP 2023 Main Conference

Unsupervised Lexical Simplification with Context Augmentation

Takashi Wada, Timothy Baldwin, Jey Han Lau

Comments 12 pages; accepted for the Findings of EMNLP 2023

An Empirical Study of Frame Selection for Text-to-Video Retrieval

Mengxia Wu, Min Cao, Yang Bai, Ziyin Zeng, Chen Chen, Liqiang Nie, Min Zhang

Comments Accepted by 2023 EMNLP findings

Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks

Po-Nien Kung, Fan Yin, Di Wu, Kai-Wei Chang, Nanyun Peng

Comments EMNLP 2023 Main

Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language

Jimin Mun, Emily Allaway, Akhila Yerukola, Laura Vianna, Sarah-Jane Leslie, Maarten Sap

Comments EMNLP 2023 Findings, 19 pages

BERTwich: Extending BERT's Capabilities to Model Dialectal and Noisy Text

Aarohi Srivastava, David Chiang

Comments Accepted for publication in Findings of the ACL: EMNLP 2023

Grounding Visual Illusions in Language: Do Vision-Language Models Perceive Illusions Like Humans?

Yichi Zhang, Jiayi Pan, Yuchen Zhou, Rui Pan, Joyce Chai

Comments Accepted at EMNLP 2023 main conference

Dataset Bias Mitigation in Multiple-Choice Visual Question Answering and Beyond

Zhecan Wang, Long Chen, Haoxuan You, Keyang Xu, Yicheng He, Wenhao Li, Noel Codella, Kai-Wei Chang, Shih-Fu Chang

Comments EMNLP 2023

Journal ref EMNLP 2023

Automatic Anonymization of Swiss Federal Supreme Court Rulings

Joel Niklaus, Robin Mamié, Matthias Stürmer, Daniel Brunner, Marcel Gygli

Comments Accepted to NLLP @ EMNLP 2023

Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy

Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal

Comments EMNLP 2023

A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization

Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, Yang You, Lidong Bing

Comments 16 pages, 3 figures

Journal ref Findings of EMNLP 2023

Multi-step Jailbreaking Privacy Attacks on ChatGPT

Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, Jie Huang, Fanpu Meng, Yangqiu Song

Comments Findings of EMNLP 2023. Updated with results on open-source LLMs

SegAugment: Maximizing the Utility of Speech Translation Data with Segmentation-based Augmentations

Ioannis Tsiamas, José A. R. Fonollosa, Marta R. Costa-jussà

Comments EMNLP 2023 (Findings)

Text-Transport: Toward Learning Causal Effects of Natural Language

Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael

Comments Accepted to EMNLP 2023

Non-Compositionality in Sentiment: New Data and Analyses

Verna Dankers, Christopher G. Lucas

Comments Published in EMNLP Findings 2023; 13 pages total (5 in the main paper, 3 pages with limitations, acknowledgments and references, 5 pages with appendices)

Defining a New NLP Playground

Sha Li, Chi Han, Pengfei Yu, Carl Edwards, Manling Li, Xingyao Wang, Yi R. Fung, Charles Yu, Joel R. Tetreault, Eduard H. Hovy, Heng Ji

Comments EMNLP Findings 2023 "Theme Track: Large Language Models and the Future of NLP"

Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users

Yohan Jo, Xinyan Zhao, Arijit Biswas, Nikoletta Basiou, Vincent Auvray, Nikolaos Malandrakis, Angeliki Metallinou, Alexandros Potamianos

Comments To Appear in EMNLP-Findings 2023

Representativeness as a Forgotten Lesson for Multilingual and Code-switched Data Collection and Preparation

A. Seza Doğruöz, Sunayana Sitaram, Zheng-Xin Yong

Comments Accepted for EMNLP'23 Findings (to appear on EMNLP'23 Proceedings)

Towards a Deep Understanding of Multilingual End-to-End Speech Translation

Haoran Sun, Xiaohu Zhao, Yikun Lei, Shaolin Zhu, Deyi Xiong

Comments Accepted to Findings of EMNLP 2023

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting

Benjamin Yan, Ruochen Liu, David E. Kuo, Subathra Adithan, Eduardo Pontes Reis, Stephen Kwak, Vasantha Kumar Venugopal, Chloe P. O'Connell, Agustina Saenz, Pranav Rajpurkar, Michael Moor

Comments Accepted to Findings of EMNLP 2023

FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactions

Hyunwoo Kim, Melanie Sclar, Xuhui Zhou, Ronan Le Bras, Gunhee Kim, Yejin Choi, Maarten Sap

Comments EMNLP 2023. Code and dataset can be found here: https://hyunw.kim/fantom

StereoMap: Quantifying the Awareness of Human-like Stereotypes in Large Language Models

Sullam Jeoung, Yubin Ge, Jana Diesner

Comments Accepted to EMNLP 2023

How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench

Qinyuan Ye, Harvey Yiyun Fu, Xiang Ren, Robin Jia

Comments Accepted to EMNLP 2023 Findings. Camera-ready version. Code: https://github.com/INK-USC/predicting-big-bench