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Logan Weber retweeted
⚡️Come check out how we scale LLM decoding parallelism! Excited to present learned asynchronous decoding with @ellieyhc for DLCT @ml_collective tomorrow at 10am PST! Thanks to @jasonyo @savvyRL for organizing.
⚡️Come check out how we scale LLM decoding parallelism! Excited to present learned asynchronous decoding with @ellieyhc for DLCT @ml_collective tomorrow at 10am PST! Thanks to @jasonyo @savvyRL for organizing.
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If you're at ICML, come check out our poster from 11:30am to 1:30pm today! We're poster #1206 in Hall C.
If you're at ICML, come check out our poster from 11:30am to 1:30pm today! We're poster #1206 in Hall C. https://t.co/qfDwwyxUud
You can find the paper here! weberlo.github.io/assets/learnin…
You can find the paper here! weberlo.github.io/assets/learnin…
Imagining the timeline where we call it "Schönfinkeling".
If you have a natural transformation between two interpretation functors, does that signal anything of interest? For the example I'm thinking of, it seems to show the source functor is "finer-grained" (separates more programs), but not sure in general.
For anyone who has experience with theorem provers and is interested in learning Lean 4, I'd recommend the slides and associated exercises here: github.com/IPDSnelting/tb…
Waaaay late on announcing this, but this fall, I'll be joining MIT as a PhD student and working with @samanprabhath and @mcarbin.
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