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cs.AI2026
Evaluating Legal Reasoning Traces with Legal Issue Tree Rubrics
Jinu Lee, Kyoung-Woon On, Simeng Han +2
Evaluating the quality of LLM-generated reasoning traces in expert domains (e.g., law) is essential for ensuring credibility and explainability, yet remains challenging due to the…
cs.AI2026
Advancing AI Research Assistants with Expert-Involved Learning
Tianyu Liu, Simeng Han, Hanchen Wang +27
Large language models (LLMs) and large multimodal models (LMMs) promise to accelerate biomedical discovery, yet their reliability remains unclear. We introduce ARIEL (AI Research A…
cs.AI2024
P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains
Simeng Han, Aaron Yu, Rui Shen +13
Existing methods on understanding the capabilities of LLMs in logical reasoning rely on binary entailment classification or synthetically derived rationales, which are not sufficie…