Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planning.

arXiv:2609.34270v1 Announce Type: cross Abstract: Interactive robot planning requires robots to infer and execute human intentions from natural language instructions that are often ambiguous, incomplete, or underspecified. Although large language models (LLMs)