Papers by Daniel Garcia
ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering (2026.acl-long)
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| Challenge: | Large language model (LLM) agents often face strict input context limits, preventing efficient consideration of large toolsets. |
| Approach: | They propose a tool that allows LLMs to merge tools with auto-correction and toolScopeRetriever to rank and select only the most relevant tools for each query. |
| Outcome: | Evaluations on three state-of-the-art LLMs and three open-source tool-use benchmarks show gains of 8.38% to 38.6% in tool selection accuracy. |