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Gengxu Li

1 accepted papers

2025

Don’t Take the Premise for Granted: Evaluating the Premise Critique Ability of Large Language Models

EMNLP 2025

Large language models (LLMs) have witnessed rapid advancements, demonstrating remarkable capabilities. However, a notable vulnerability persists: LLMs often uncritically accept flawed or contradictory premises, leading to inefficient reasoning and unreliable outputs. This emphasizes the significance