Papers by Junkai Tong
Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction (2025.emnlp-main)
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Junkai Liu, Yujie Tong, Hui Huang, Bowen Zheng, Yiran Hu, Peicheng Wu, Chuan Xiao, Makoto Onizuka, Muyun Yang, Shuyuan Zheng
| Challenge: | Existing studies use legal facts to predict judgments, but legal facts are difficult to obtain in early stages of litigation. |
| Approach: | They propose a legal fact prediction task that takes evidence from trial as input to make predictions in the absence of ground-truth legal facts. |
| Outcome: | The proposed task can predict court rulings without ground-truth legal facts . the first benchmark dataset, LFPBench, is used to evaluate the task . |
SecCoder: Towards Generalizable and Robust Secure Code Generation (2024.emnlp-main)
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| Challenge: | Existing secure code generation methods have limited generalizability to unseen test cases and poor robustness against the attacked model, leading to safety failures in code generation. |
| Approach: | They propose a generalizable and robust secure code generation method SecCoder by using in-context learning and the safe demonstration. |
| Outcome: | The proposed method achieves a significant security improvement of 7.20% on unseen test cases and better robustness against the attacked model. |