Author

Timothy M. Hospedales

2 papers indexed here

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#artificial intelligence Dec 2025

The Reward Model Selection Crisis in Personalized Alignment

The findings reveal that the field has been optimizing for proxy metrics that do not predict deployment performance, and that current personalized alignment methods fail to operationalize preferences into behavioral adaptation under realistic deployment constraints, and finds simple in-context learning (ICL) to be high...

Fady Rezk, Yuangang Pan, Chuan-Sheng Foo et al. · arXiv.org · 3 citations

#artificial intelligence Preprint Sep 2026

Metro-WM: Long-Horizon Latent Planning with Realisable Sub-Goals

Metro-WM is introduced, a hierarchical framework that issues sub-goals by retrieving genuine states from prior experience rather than generating ungrounded latent vectors that achieves superior long-horizon success rates and maintains robust performance under extremely sparse dataset conditions.

Royson Lee, Fady Rezk, Titouan Parcollet et al. · 0 citations