Publications

1. Language Models are Symbolic Learners in Arithmetic
   Chunyuan Deng, Zhiqi Li, Roy Xie, Ruidi Chang, Hanjie Chen
   Preprint. [arXiv]


2. MiCEval: Unveiling Multimodal Chain of Thought's Quality via Image Description and Reasoning Steps
   Xiongtao Zhou*, Jie He*, Lanyu Chen, Jingyu Li, Haojing Chen, Victor Gutierrez Basulto, Jeff Z. Pan, Hanjie Chen
   Preprint. [arXiv]


3. From Babbling to Fluency: Evaluating the Evolution of Language Models in Terms of Human Language Acquisition
   Qiyuan Yang*, Pengda Wang*, Luke D. Plonsky, Frederick L. Oswald, Hanjie Chen
   Preprint. [arXiv]


4. SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
   Haotian Xia, Zhengbang Yang, Junbo Zou, Rhys Tracy, Yuqing Wang, Chi Lu, Christopher Lai, Yanjun He, Xun Shao, Zhuoqing Xie, Yuan-fang Wang, Weining Shen, Hanjie Chen
   Preprint. [arXiv]


5. Language and Multimodal Models in Sports: A Survey of Datasets and Applications
   Haotian Xia, Zhengbang Yang, Yun Zhao, Yuqing Wang, Jingxi Li, Rhys Tracy, Zhuangdi Zhu, Yuan-fang Wang, Hanjie Chen, Weining Shen
   Preprint. [arXiv]


6. Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions
   Hanjie Chen*, Zhouxiang Fang*, Yash Singla, Mark Dredze
   Preprint. [arXiv]


7. Will the Real Linda Please Stand up...to Large Language Models? Examining the Representativeness Heuristic in LLMs
   Pengda Wang*, Zilin Xiao*, Hanjie Chen, Frederick L. Oswald
   The First Conference on Language Modeling (COLM), Philadelphia, Pennsylvania, United States, Oct. 2024.
   Oral Spotlight (top 2%) [Paper] [Code]


8. RORA: Robust Free-Text Rationale Evaluation
   Zhengping Jiang*, Yining Lu*, Hanjie Chen, Daniel Khashabi, Benjamin Van Durme, Anqi Liu
   The 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Bangkok, Thailand, Aug. 2024. [Paper] [Code]


9. Explanation in the Era of Large Language Models
   Zining Zhu, Hanjie Chen, Xi Ye, Chenhao Tan, Ana Marasović, Sarah Wiergreffe, Veronica Qing Lyu
   2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) Tutorial, Mexico City, Mexico, Jun. 2024. [Abstract] [Website]


10. Explainability for Large Language Models: A Survey
    Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
    ACM Transactions on Intelligent Systems and Technology, Jan. 2024. [Paper]


11. REV: Information-Theoretic Evaluation of Free-Text Rationales
    Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi, and Swabha Swayamdipta
    The 61st Annual Meeting of the Association for Computational Linguistics (ACL), Toronto, Canada, Jul. 2023
    [Acceptance Rate: 1074/4864≈22%][Paper] [Code]


12. KNIFE: Knowledge Distillation with Free-Text Rationales
    Aaron Chan*, Zhiyuan Zeng*, Wyatt Lake, Brihi Joshi, Hanjie Chen, Xiang Ren
    Preprint. [arXiv]


13. Neural Model Interpretability for Natural Language Processing
    Hanjie Chen
    PhD Dissertation, May 2023. [Abstract]


14. Improving Interpretability via Explicit Word Interaction Graph Layer
    Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi
    The 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, USA, Feb. 2023.
    [Acceptance Rate: 1721/8777≈19.6%][Paper][Code]


15. Explaining Predictive Uncertainty by Looking Back at Model Explanations
    Hanjie Chen, Wanyu Du, Yangfeng Ji
    AAAI Workshop on Uncertainty Reasoning and Quantification in Decision Making, Feb. 2023. [Paper]


16. Identifying the Source of Vulnerability in Explanation Discrepancy: A Case Study in Neural Text Classification.
    Ruixuan Tang, Hanjie Chen, Yangfeng Ji
    EMNLP BlackboxNLP Workshop, Dec. 2022 [Paper]


17. Self-training with Two-phase Self-augmentation for Few-shot Dialogue Generation
    Wanyu Du, Hanjie Chen, Yangfeng Ji
    Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), Abu Dhabi, Dec. 2022. [Paper][Code]


18. Pathologies of Pre-trained Language Models in Few-shot Fine-tuning
    Hanjie Chen, Guoqing Zheng, Ahmed Hassan Awadallah, Yangfeng Ji
    ACL Workshop on Insights from Negative Results in NLP, Dublin, Ireland, May 2022. [Paper]


19. Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation
    Hanjie Chen, Yangfeng Ji
    The 36th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, BC, Canada, Feb. 2022.
    [Acceptance Rate: 1349/9020≈15%, Oral Presentation (top 1.5%)] [Paper] [Code]


20. Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing
    Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi
    EMNLP BlackboxNLP Workshop, Nov. 2021 [Paper]


21. Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks
    Hanjie Chen, Song Feng, Jatin Ganhotra, Hui Wan, Chulaka Gunasekara, Sachindra Joshi, Yangfeng Ji
    2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Jun. 2021
    [Acceptance Rate: 477/1797≈26.5%] [Paper] [Code]


22. Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers
    Hanjie Chen, Yangfeng Ji
    The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov. 2020
    [Acceptance Rate: 754/3359≈22.4%] [Paper] [Code]


23. Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection
    Hanjie Chen, Guangtao Zheng, Yangfeng Ji
    The 58th Annual Meeting of the Association for Computational Linguistics (ACL), July 2020
    [Acceptance Rate: 779/3429≈22.7%] [Paper] [Code]


24. Improving the Explainability of Neural Sentiment Classifiers via Data Augmentation
    Hanjie Chen, Yangfeng Ji
    NeurIPS 2019 Workshop on Robust AI in Financial Services, Dec. 2019 [Paper]