Papers by Wenjun Tan

2 papers
Reasoning Like a Doctor: Improving Medical Dialogue Systems via Diagnostic Reasoning Process Alignment (2024.findings-acl)

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Challenge: Medical dialogue systems have attracted significant attention for their potential to act as medical assistants.
Approach: They propose a framework that emulates clinicians' diagnostic reasoning processes and aligns with clinician preferences through thought process modeling.
Outcome: The proposed framework generates appropriate responses that relies on abductive and deductive diagnostic reasoning analyses and aligns with clinician preferences through thought process modeling.
Semantic-Eval : A Semantic Comprehension Evaluation Framework for Large Language Models Generation without Training (2025.acl-long)

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Challenge: Large language models (LLMs) have emerged as key drivers of progress in the field of natural language processing.
Approach: They propose a framework that assesses LLM-generated text based on semantic understanding.
Outcome: The proposed framework surpasses traditional evaluation metrics and lags behind GPT-4.

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