| 2026 | ACL | CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment. | Radin Shayanfar, Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2025 | EMNLP | Towards Low-Resource Alignment to Diverse Perspectives with Sparse Feedback. | Chu Fei Luo, Samuel Dahan, Xiaodan Zhu |
| 2024 | EMNLP | Misinformation with Legal Consequences (MisLC): A New Task Towards Harnessing Societal Harm of Misinformation. | Chu Fei Luo, Radin Shayanfar, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2023 | ACL | Prototype-Based Interpretability for Legal Citation Prediction. | Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2023 | EMNLP | Legally Enforceable Hate Speech Detection for Public Forums. | Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2023 | JURIX | OpenJustice.ai: A Global Open-Source Legal Language Model. | Samuel Dahan, Rohan Bhambhoria, David Liang, Xiaodan Zhu |
| 2022 | AAAI | Interpretable Low-Resource Legal Decision Making. | Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu |
| 2022 | AI | Evaluating Explanation Correctness in Legal Decision Making. | Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2021 | AI | Investigating the State-of-the-Art Performance and Explainability of Legal Judgment Prediction. | Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu |
| 2020 | DASC | Determining Worker Type from Legal Text Data using Machine Learning. | Yifei Yin, Farhana H. Zulkernine, Samuel Dahan |
| 2020 | KDD | The Gap between Deep Learning and Law: Predicting Employment Notice. | Jason T. Lam, David Liang, Samuel Dahan, Farhana H. Zulkernine |