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Princeton University
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CoMet reveals that decomposing uncertainty into context and multiplicity components can lead to substantial improvements in uncertainty estimation for multimodal AI systems.
Fast weight models can now achieve significantly better long-context performance thanks to a new RL training framework that moves beyond next-token prediction.
