LLM-as-a-Verifier uses continuous scores to improve agent evaluation
solyarisoftware · x · 2026-07-22
LLM-as-a-Verifier proposes training-free verification for agentic tasks
The paper introduces LLM-as-a-Verifier, a general-purpose framework that improves agent evaluation without additional training. Instead of relying on discrete judge labels, it uses continuous scores from scoring-token logits to obtain more granular verification signals.
The authors report that verification quality improves when they:
- use finer score granularity,
- repeat evaluations,
- decompose criteria into smaller parts.
They say the approach boosts accuracy across coding, robotics, and medical benchmarks, and is aimed at scaling verification more reliably for agentic workflows.
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