Papers by Hanlin Xue

2 papers
Domaino1s: Guiding LLM Reasoning for Explainable Answers in High-Stakes Domains (2025.findings-acl)

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Challenge: Existing Large Language Models (LLMs) generate brief answers without reasoning processes and explanations.
Approach: They propose supervised fine-tuning and tree search to enhance LLMs’ reasoning capabilities on domain tasks.
Outcome: The proposed model improves on stock investment recommendation and legal reasoning QA tasks.
Verifiable LLM-Generated Text Detection via Projected Semantic-Structural Distributions (2026.acl-long)

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Challenge: Existing methods for detecting LLM-Generated text suffer from distribution misalignment and limited interpretability.
Approach: They propose a statistical framework utilizing supervised subspace learning to extract compact features and construct conditional semantic distributions based on syntactic structures.
Outcome: The proposed framework is superior in cross-domain, cross-model, and adversarial scenarios.

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