Papers by Yihong Pan

2 papers
LegalChainReasoner: Grounding Criminal Judicial Opinion Generation via Structured Legal Chains (2026.acl-long)

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Challenge: Current legalAI tasks divide sentencing and legal reasoning into two separate tasks, resulting in inconsistency between the reasoning and predictions.
Approach: They propose a new task that generates both legal reasoning and sentencing decisions using a framework that applies structured legal chains to guide the model through comprehensive case assessments.
Outcome: The proposed model outperforms baseline models on real-world, open-source Chinese legal case datasets.
DefGen-Bench: A Benchmark for Chinese Criminal Defence Opinion Generation in LegalAI (2026.acl-long)

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Challenge: Existing LegalAI tasks are descriptive or predictive, requiring the users to translate the information into legal reasoning.
Approach: They propose a task to generate a structured defence opinion conditioned jointly on an indictment and the defendant’s stated opinion, which often present conflicting claims.
Outcome: The proposed approach improves on eight large language models (LLMs) and shows that it is more efficient than previous approaches.

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