arXiv AI August 20, 2026 By Andrei Cristian Popescu, Haitz S\'aez de Oc\'ariz Borde, Pietro Li\`o

Looped Language Models Improve Compositional Tool Calling

The paper investigates the use of looped language models for compositional tool calling, where models must coordinate multiple API calls and maintain state across interactions. Experiments on API-Bank, BFCL, and NESTful show that recurrent computation generally improves compositional and dependency-aware tool use, with accuracy increasing as recurrent depth grows. Adaptive inference offers a better compute‑performance trade‑off by allocating extra computation only when necessary.

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