Researchers at an undisclosed institution found that multi-teacher on-policy distillation for agentic language models can cause over-calling of tools, where models call tools on examples that should b…
Researchers at arXiv identified a silent policy-violation failure mode in tool-using LLM agents, where tools execute forbidden state transitions without error signals. In the τ²-bench airline domain, …
A developer analyzed the open-source ecosystem for reducing LLM costs, focusing on three cost lines: cached input, uncached/written input, and output. The key insight is that tools must preserve the m…
Kitchen Rush, a new benchmark for evaluating large language model tool-calling, measures both accuracy and latency by simulating an Overcooked-style kitchen where thinking time directly impacts game p…