MagicSelector uses counterfactual decomposition to improve agent tool selection
_reachsumit · x · 2026-07-21
MagicSelector studies how to improve agent tool selection.
The method combines:
- Counterfactual task decomposition
- Progressive reranking driven by hard negatives
- Dynamic top-K truncation for tool retrieval
The goal is to make agents pick better tools more reliably by improving retrieval and ranking over candidate tools.
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