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@dogacel0
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Excited to announce our work "Attention Drift" has been accepted to NeurIPS 2026 🎉
I'm so happy to see our method's widespread adoptation. Now supported by all major inference engines, vLLM, Tokenspeed, SGLang and TRT-LLM. Also community trained speculative decoding models for Minimax M3 (@inferact and @AMD) and Kimi K2.6-K3 trained (@lightseekorg) being served in production as EAGLE 3.1
Shout out to all the great team mebers @themishtimoi @yigitcancomlek @kaan_oktay @hongyangzh and Stephen Xia.
And special thanks to @fal for helping for making this research possible 🙂
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is one of the coolest projects I've seen. It automatically reproduces results in a paper using agents that automatically spin up GPUs on cloud. I've just sent my most recent paper and it automatically reproduced it end to end 🙂
@askalphaxiv
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The first major project I worked on since joining @fal is live. We've optimized everything from the bottom up: custom kernels, infra and a distilled model ⚡️
We even optimized LLMs for near real-time prompt expansion, more details soon 🙂
Kudos to @y8hann and @akaan_akan
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