LLM-as-a-Verifier: A General-Purpose Verification Framework | alphaXiv

Researchers from Stanford, UC Berkeley, and NVIDIA Research developed LLM-as-a-Verifier, a training-free framework that leverages fine-grained logit distributions for continuous feedback,...

Abstract Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the ability to determine the correctness of a solution, as a new scaling axis. To unlock this and demonstrate its effectiveness, we introduce LLM-as-a-Verifier, a general-purpose verification framework that provides fine-grained feedback for agentic tasks without requiring additional training. Unlike standard LM judges that prompt LLMs to produce discrete scores for candidate solutions, LLM-as-a-Verifier computes t

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• Ziran Yang

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