Audit finds 36-39% incorrect FOL labels in FOLIO and MALLS; corrections raise LLM accuracy 9-22 points and an LLM-guided review framework achieves 90% dataset quality after checking fewer than 24% of examples.
P - FOLIO : Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains
2 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
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cs.CL 2years
2026 2representative citing papers
LLMEval-Logic is a solver-verified Chinese logical reasoning benchmark with 246 base and 190 hard items that shows frontier LLMs reach only 37.5% hard-item accuracy and 60.16% joint formalization score.
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LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening
LLMEval-Logic is a solver-verified Chinese logical reasoning benchmark with 246 base and 190 hard items that shows frontier LLMs reach only 37.5% hard-item accuracy and 60.16% joint formalization score.