Kanaka Rajan
@kanakarajanphd.bsky.social did:plc:nemx43ymm6toi4fqil4gqbev
Associate Professor at Harvard & Kempner Institute. Applying computational frameworks & machine learning to decode multi-scale neural processes. Marathoner. Rescue dog mom. https://www.rajanlab.com/
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Kanaka Rajan (@kanakarajanphd.bsky.social) es un usuario de Bluesky que se unió el 11 septiembre 2023. Tiene 3.785 seguidores, sigue a 248 cuentas y ha publicado 61 posts.
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📄 Paper: arxiv.org/abs/2609.38081 🌐 Page: ann-huang-0.github.io/Hessian-null... 💻 Code: github.com/Ann-Huang-0/hessian-null-space-continuation w/ my awesome team 🌟 @neurostrow.bsky.social, @hansonlu.bsky.social @wtredman.bsky.social, @leokoz8.bsky.social, @kanakarajanphd.bsky.social (12/12)
Ver postOverall, HNC finds diverse mechanisms with matched function around a single trained network. This opens the door to mechanistic analysis of solution spaces, to separating task demands from optimizer bias, and to a principled basis for reward auditing, model merging, editing and fine-tuning (11/12)
Ver post📐 HNC also measures loss-landscape geometry. The Hessian captures the local geometry around one network; the null space walk tracks how it changes along the way. Bigger models have more flat directions, while harder tasks have fewer. The directions HNC follows get stiffer on harder tasks. (10/12)
Ver postHNC can also uncover reward hacking! In the AI Safety Gridworld boat race, we start with policies that correctly follow the track. Preserving proxy reward (+3 for entering an arrow tile clockwise), HNC walks find the known exploit: hopping on and off one tile without net clockwise progress (9/12)
Ver postApplied to RL, HNC searches for different policies while preserving a reward surrogate. An odor-tracking agent shifts from zigzagging across a plume to smoothly following its edge—a distinct navigation strategy at comparable return 🪰(8/12)
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