A Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding

arXiv:2607.07974v1 Announce Type: new Abstract: Intent detection is a critical task that bridges human intents and system actions in human-machine interaction systems. However, there still exist challenges for detecting out-of-scope (OOS) intents. (i) The traditional methods view the OOS intent detection as a multi-class classification, then the detection accuracy decreases as the class number of the known intents increases; (ii) LLM-embedding methods require large parameters, that makes them di...