Author

Chu-Chu Fan

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#artificial intelligence Preprint Oct 2026

RECAST: Learning to Compute the Right Context through Adaptive Evidence Routing

Large language models are increasingly applied to tasks grounded in long, heterogeneous information sources. Conventional Retrieval-Augmented Generation (RAG) relies on fixed similarity-based retrieval, while agentic variants adapt queries and tool use but remain largely retrieval-centric. However, in many tasks, the e...

Yi-Lun Hao, Krishna Sayana, Isabella Ye et al. · 0 citations

#artificial intelligence Preprint Sep 2026

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. · 0 citations