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Research questionHow can LLMs interleave reasoning with reliable step-level self-critique without a separate verifier?LLMs may produce plausible reasoning without detecting mistakes until the final answer. Separate verifiers can provide feedback, but they add coordination and system complexity, while self-critique must remain aligned with actual reasoning correctness.
AI
Evaluation & Benchmarks
LLM Pretraining & Post-training
Natural Language Processing
Reasoning
Reinforcement Learning
Latest papersRecent research connected to this question, newest first.Stepwise Think-Critique: Interleaved Reasoning and Self-Critique in a Single LLMThe source studies a single 1.5B-parameter LLM that emits structured critiques inline with each reasoning step and is trained using reasoning and critique-consistency rewards. Evidence comes from five mathematical reasoning benchmarks, including comparisons with external process reward models at dataset-specific oracle thresholds.research paper · Sep 2, 2026
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