dailyai.report

The ToolSense framework exposes a gap between tool retrieval performance and actual understanding in LLMs. Researchers found that standard benchmarks rely on constrained decoding, masking a model's inability to reason about tool semantics. This diagnostic tool forces models to prove knowledge without shortcuts. Practitioners can now better validate agent reliability before deployment.