Tool-Adaptive LLM Reranker
_reachsumit · x · 2026-07-14
The Tool-Adaptive LLM Reranker paper reformulates pointwise reranking as an agentic decision process.
Instead of deterministically scoring each candidate, the model autonomously decides when to invoke external search tools based on the current sample and cost constraints. Training utilizes cost-aware reinforcement learning rewards to strike a balance between accuracy and latency.
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