CLINC150

A new arXiv study (2608.20371v1) comparing zero-shot Claude Haiku against fine-tuned NLU models for intent detection finds that fine-tuned RoBERTa beats Claude by 11.8 points on ATIS (95.9 vs. 84.1, p…

Researchers developed a new method for out-of-scope intent detection using MiniLM embeddings, treating it as a one-class classification task with multi-cluster boundary learning. The approach outperfo…

Researchers propose a multi-cluster boundary learning method for out-of-scope intent detection using MiniLM embedding, achieving state-of-the-art performance on CLINC150, StackOverflow, and Banking77 …