Critic-R uses a critic model for natural-language introspective feedback to refine queries at inference time and optimize retrievers from successful/failed trajectories on multi-hop QA tasks.
D Critic-Embed Training Details Critic-Embed is initialized from Stella-400M em- bedding model (Zhang et al., 2025a) 7 and fine- tuned with InfoNCE (temperature τ= 0.02 )
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Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback
Critic-R uses a critic model for natural-language introspective feedback to refine queries at inference time and optimize retrievers from successful/failed trajectories on multi-hop QA tasks.