Jay Shenoy

4 posts

Jay Shenoy

Jay Shenoy

@jayrshenoy

CS PhD @StanfordAILab

Katılım Temmuz 2017
309 Takip Edilen41 Takipçiler
Jay Shenoy
Jay Shenoy@jayrshenoy·
@GordonWetzstein Excited by the new directions enabled by this idea, training next-gen models directly on experimental data
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Gordon Wetzstein
Gordon Wetzstein@GordonWetzstein·
AlphaFold-based models like Boltz-2 and BioEmu train on atomic conformational structures in order to predict protein dynamics. But is it possible to train these models directly on cryo-EM map ensembles, harnessing conformational data that is typically not deposited in the PDB? Introducing CryoSampler: a new approach for fine-tuning Boltz-2 with raw supervision on cryo-EM map ensembles. 1/6🧵
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Michael Y. Li
Michael Y. Li@michaelyli_·
Can a language model learn, end-to-end, what to keep in its own KV cache and what to throw away? Can it learn to forget while it learns to reason? Deep learning's central lesson: capability emerges from end-to-end optimization, not heuristics/strong inductive biases. But for efficiency, we rely heavily on hand-designed approaches. 🗑️ Introducing Neural Garbage Collection (NGC): we train a language model to jointly reason and manage its own KV cache, using reinforcement learning with outcome-based task reward alone. No SFT, no proxy objectives, no summarization in natural language. New paper with @jubayer_hamid, Emily Fox, and @noahdgoodman!
Michael Y. Li tweet media
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