Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planning
This work proposes a Bayesian framework that treats clarification as an active learning problem over grounded Signal Temporal Logic task specifications and uses LLMs to initialize candidate formal specifications and translate informative contrasts into natural-language clarification questions, while Bayesian optimizati...
Hu-Ao Li, Carson Sobolewski, A. Saravanos et al.
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