Capturing LLM Capabilities via Evidence-Calibrated Query Clustering 事件

Capturing LLM Capabilities via Evidence-Calibrated Query Clustering arXiv:2605.17110v2 Announce Type: replace Abstract: Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing clustering methods, which primarily rely on semantic taxonomies or embeddings, often fail to capture such latent capability requirements due to a misalignment between surface-level semantics and actual model performance. We propose EC