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arXiv cs.CL
arXiv cs.CL
7/10/2026
A Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding

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

Short summary

Proposes a multi-cluster boundary learning method for detecting out-of-scope intents in conversational AI using MiniLM embeddings. Addresses performance degradation in traditional multi-class classification as the number of known intent classes increases. Achieves state-of-the-art results on public benchmarks with reproducible code.

  • •New method for out-of-scope intent detection using lightweight MiniLM embeddings
  • •Solves scalability problem: performance no longer degrades with more known intent classes
  • •State-of-the-art results on CLINC150, StackOverflow, Banking77 datasets; code available

Generated with AI, which can make mistakes.

#research-breakthrough#ai-tools#open-source
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