Papers by Linchen Xiao

2 papers
CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward (2025.emnlp-main)

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Challenge: Existing approaches lack robustness to handle complex edge cases and generalizability across different domains.
Approach: They develop an accurate and lightweight verifier model for evaluation and outcome reward that matches unstructured outputs against standard answers.
Outcome: The proposed model can process multiple answer types including multi-subproblems, formulas, and sequence answers while identifying abnormal/invalid responses.
Are Your LLMs Capable of Stable Reasoning? (2025.findings-acl)

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Challenge: Existing evaluation protocols and metrics do not capture the full spectrum of LLM capabilities, especially in complex reasoning tasks.
Approach: They propose a new evaluation metric that continuously assesses model performance across multiple sampling attempts, quantifying both the model’s potential capabilities and operational consistency.
Outcome: The proposed evaluation metric measures model performance across multiple sampling attempts and provides comprehensive insights into their potential capabilities and operational consistency.

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