Papers by Zengzhi Wang

1 papers
Ask Again, Then Fail: Large Language Models’ Vacillations in Judgment (2024.acl-long)

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Challenge: Existing large language models often waver in their judgments when faced with follow-up questions . this is a challenge for generating reliable responses and building user trust .
Approach: They propose a Follow-up Questioning Mechanism and two metrics to quantify this inconsistency . they also develop a framework that teaches large language models to maintain original correct judgments .
Outcome: The proposed framework improves the general capabilities of large language models by allowing them to maintain original correct judgments.

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