CCTU: A Benchmark for Tool Use under Complex Constraints
Quick summary
arXiv:2603.15309v2 Announce Type: replace-cross Abstract: Solving problems through tool use under explicit constraints constitutes a highly challenging yet unavoidable scenario for large language models (LLMs), requiring capabilities such as function calling, instruction following, and self-refinement. However, progress has been hindered by the absence of dedicated evaluations. To address this, we introduce CCTU, a benchmark for evaluating LLM tool use under complex constraints. CCTU is grounded in a taxonomy of 12 constraint categories spanning four dimensions (i.e., resource, behavior, tools
Key takeaways
- arXiv:2603.15309v2 Announce Type: replace-cross Abstract: Solving problems through tool use under explicit constraints constitutes a highly challenging yet unavoidable scenario for large language models (LLMs), requiring capabilities such as function calling, instruction following, and self-refinement.
- However, progress has been hindered by the absence of dedicated evaluations.
- To address this, we introduce CCTU, a benchmark for evaluating LLM tool use under complex constraints.
Why it matters
“CCTU: A Benchmark for Tool Use under Complex Constraints” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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