W. Chen

When an AI agent calls an external tool, retrieval previously ranked candidates by semantic relevance alone and could not tell whether a tool would actually work at runtime. RATED pairs a frozen dual-encoder for semantic matching with a lightweight contextual bandit that re-ranks candidates from each execution's success or failure feedback. Under 30% failure injection, fault selection drops from 86.2% for the ToolLLM API retriever to 2.9%, at 0.172 ms added latency per step.

When an AI agent calls an external tool, retrieval previously ranked candidates by semantic relevance alone and could not tell whether a tool would actually work at runtime. RATED pairs a frozen dual-encoder for semantic matching with a lightweight contextual bandit that re-ranks candidates from each execution's success or failure feedback. Under 30% failure injection, fault selection drops from 86.2% for the ToolLLM API retriever to 2.9%, at 0.172 ms added latency per step.