In the memory constrained world we are running into, these kinds of insights are key.

Giovanni Monea@giomonea.bsky.social · 4w ago

⚠️ Stop pretraining your looped Transformer with a separate KV cache per recursion! In our recent preprint, we show that *memory sharing* not only saves memory but is also a net-positive inductive bias! Less memory, same flops, higher quality. 🔗 arxiv.org/abs/2610.02383 🧵

⚠️ Stop pretraining your looped Transformer with a separate KV cache per recursion! In our recent preprint, we show that *memory sharing* not only saves memory but is also a net-positive inductive bias! Less memory, same flops, higher quality. 🔗 arxiv.org/abs/2610.02383 🧵

A bit of a mess around the conflict of COLM with the ARR (and to lesser degree ICML) reviews release. We feel this is creating a lot of pressure and uncertainty. So, we are pushing our deadlines: Abstracts due March 22 AoE (+48hr) Full papers due March 28 AoE (+24hr) Plz RT 🙏

Please repost to get the word out! @nkgarg.bsky.social and I are excited to present a personalized feed for academics! It shows posts about papers from accounts you’re following bsky.app/profile/pape...

We recently pushed an update to our in-context RL paper. Usually, updates don't justify a post, but this one is exceptionally contentful -> 🧵 tl;dr: all the findings are stronger, and the behaviors are super cool! arxiv.org/abs/2410.05362