Small Agents with Semantic Search: Efficient Multilingual Code Localization
Locating relevant files from natural-language requests is a core subtask for agents operating over code repositories. We investigate whether this task can be delegated to compact, specialized models to enable on-device search while reducing the token usage, latency, and inference cost of larger agents. We show that semantic search improves file localization, with gains in accuracy, cross-language transfer, and inference efficiency. To study this setting, we introduce a training framework for file-localization agents built around ColGREP, a local semantic search tool based on late-interaction retrieval models. Our recipe combines weighted supervised fine-tuning on teacher trajectories, ass...
| Authors | Maxence Lasbordes, Aarush Sinha, Raphael Sourty et al. |
|---|---|
| Primary category | cs.CL |
| Published | 4 October 2026 |
| Last updated at source | 4 October 2026 |
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