Publications

2024

[32] Mechanisms of non-factual hallucinations in language models
Yu Lei, Meng Cao, JCK Cheung, Yue Dong
EMNLP 2024 Findings
[31] Adversarial Attacks on Parts of Speech: An Empirical Study in Text-to-Image Generation
GM Shahariar, Jia Chen, Jiachen Li, Yue Dong
EMNLP 2024 Findings
[30] How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrieval
Fengran Mo, Longxiang Zhao, Kaiyu Huang, Yue Dong, Degen Huang, Jian-Yun Nie
CIKM 2024
[29] IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models
Haz Sameen Shahgir, Khondker Salman Sayeed, Abhik Bhattacharjee, Wasi Uddin Ahmad, Yue Dong, Rifat Shahriyar
Conference on Language Modeling (COLM) 2024
[28] Safety Alignment in NLP Tasks: Weakly Aligned Summarization as an In-Context Attack
Yu Fu, Yufei Li, Wen Xiao, Cong Liu, Yue Dong
ACL 2024
[27] Source-Free Domain Adaptation for Question Answering with Masked Self-training
Maxwell Yin, Boyu Wang, Yue Dong, Charles Ling
TACL 2024
[26] Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong
ACL Findings 2024
[25] Cross-Modal Safety Alignment: Is textual unlearning all you need?
Trishna Chakraborty, Erfan Shayegani, Zikui Cai, Nael Abu-Ghazaleh, M Salman Asif, Yue Dong, Amit Roy-Chowdhury, Chengyu Song
EMNLP 2024 Findings
[24] Subtle Misogyny Detection and Mitigation: An Expert-Annotated Dataset
Brooklyn Sheppard, Anna Richter, Allison Cohen, Elizabeth Allyn Smith, Tamara Kneese, Carolyne Pelletier, Ioana Baldini, Yue Dong
ACL Findings 2024
[23] Cross-task defense: Instruction-tuning LLMs for content safety
Yu Fu, Wen Xiao, Jia Chen, Jiachen Li, Evangelos Papalexakis, Aichi Chien, Yue Dong
TrustNLP Workshop @ NAACL 2024
[22] PAT-Questions: A Self-Updating Benchmark for Present-Anchored Temporal Question-Answering
Jannat Ara Meem, Muhammad Shihab Rashid, Yue Dong, Vagelis Hristidis
ACL Findings 2024
[21] EcoRank: Budget-Constrained Text Re-ranking Using Large Language Models
Muhammad Shihab Rashid, Jannat Ara Meem, Yue Dong, Vagelis Hristidis
ACL Findings 2024
[20] Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models
Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh
ICLR 2024 (Spotlight), Best Paper Award at 2023 SoCal NLP Symposium
[19] Watermarking conditional text generation for AI detection: Unveiling challenges and a semantic-aware watermark remedy
Yu Fu, Deyi Xiong, Yue Dong
AAAI 2024

2023

[18] Subtle Misogyny Detection and Mitigation: An Expert-Annotated Dataset
Brooklyn Sheppard, Anna Richter, Allison Cohen, Elizabeth Allyn Smith, Tamara Kneese, Carolyne Pelletier, Ioana Baldini, Yue Dong
NeurIPS 2023 SoLaR Workshop (Spotlight)
[17] Inverse Reinforcement Learning for Text Summarization
Yu Fu, Deyi Xiong, Yue Dong
Findings of EMNLP 2023

2022

[16] Faithful to the Document or to the World? Mitigating Hallucinations via Entity-Linked Knowledge in Abstractive Summarization
Yue Dong, John Wieting, Pat Verga
Findings of EMNLP 2022
[15] Learning with Rejection for Abstractive Text Summarization
Meng Cao, Yue Dong, Jingyi He, Jackie Chi Kit Cheung
EMNLP 2022
[14] Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
Meng Cao, Yue Dong, Jackie C. K. Cheung
ACL 2022

2021

[13] On-the-Fly Attention Modulation for Neural Generation
Yue Dong, Chandra Bhagavatula, Ximing Lu, Jena D. Hwang, Antoine Bosselut, Jackie C. K. Cheung, Yejin Choi
Findings of ACL 2021
[12] Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
ACL 2021
[11] Discourse-Aware Unsupervised Summarization for Long Scientific Documents
Yue Dong, Andrei Romascanu, Jackie C. K. Cheung
EACL 2021

2020

[10] Multi-Fact Correction in Abstractive Text Summarization
Yue Dong, Shuohang Wang, Zhe Gan, Yu Cheng, Jackie C. K. Cheung, Jingjing Liu
EMNLP 2020
[9] Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Yao Lu, Yue Dong, Laurent Charlin
EMNLP 2020
[8] Factual Error Correction for Abstractive Summarization Models
Meng Cao, Yue Dong, Jiapeng Wu, Jackie C. K. Cheung
EMNLP 2020

2019

[7] Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses
Yue Dong, Matt Grenander, Jackie C. K. Cheung, Annie Louis
EMNLP-IJCNLP 2019
[6] EditNTS: A Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
Yue Dong, Zichao Li, Mehdi Rezagholizadeh, Jackie C. K. Cheung
ACL 2019 (Oral)
[5] Learning Multi-task Communication with Message Passing for Sequence Learning
Pengfei Liu, Yue Dong, Jie Fu, Xipeng Qiu, Jackie C. K. Cheung
AAAI 2019

Before 2018

[4] BanditSum: Extractive Summarization as a Contextual Bandit
Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie C. K. Cheung
EMNLP 2018 (Oral)
[3] A Hierarchical Neural Attention-based Text Classifier
Koustuv Sinha, Yue Dong, Jackie C. K. Cheung, Derek Ruths
EMNLP 2018
[2] Threaded ensembles of autoencoders for stream learning
Yue Dong, Nathalie Japkowicz
Computational Intelligence 2018
[1] Threaded ensembles of supervised and unsupervised neural networks for stream learning
Yue Dong, Nathalie Japkowicz
Canadian Conference on Artificial Intelligence 2016 (Best Paper Award)

Yue Dong
Yue Dong
Assistant Professor

Yue Dong is an assistant professor of computer science and engineering at the University of California Riverside. Her research interests include natural language processing, machine learning, and artificial intelligence. She leads the Natural Language Processing group, which develops natural language understanding and generation systems that are controllable, trustworthy, and efficient.