John Cooper

5 posts

John Cooper

John Cooper

@jfrcooper2

PhD Researcher as UW Madison working on hybrids, W2S generalization, and safety.

Monona, WI Katılım Aralık 2024
54 Takip Edilen20 Takipçiler
John Cooper retweetledi
Avi Trost✈️ ICML
Avi Trost✈️ ICML@atrost3122·
Today we’ll present our work Fully Nested Transformers at AdaptFM ICML workshop! Find us at poster session 2 at 2:30 (poster # TBD), happy to chat :)
Avi Trost✈️ ICML@atrost3122

Nested models let you train a whole family of submodels at once. What if you could use them all at once, too? Block triangular weights enable this structure. It gives us token-adaptive routing, self-speculative decoding, and more. Introducing: Fully Nested Transformers (1/9)

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John Cooper retweetledi
Albert Ge
Albert Ge@albert_ge_95·
Our newly accepted #COLM2026 paper explains how & why LLMs fail at large optimization tasks (1000s of variables). We show how to fix these issues while being efficient with token usage. 🧵
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John Cooper
John Cooper@jfrcooper2·
If you miss us, message me or send an email! We’d be happy to talk after the conference as well. My wonderful coauthors: Ilias Diakonikolas, Mingchen Ma, @fredsala!
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John Cooper
John Cooper@jfrcooper2·
Excited to be presenting an oral and poster at #ICML2026 about hybrid models and their capabilities! There have been many empirical results, but far too few theoretical ones explaining their expressivity. We show there are tasks with a separation! Come chat! Oral 6A, poster 4622.
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John Cooper retweetledi
Avi Trost✈️ ICML
Avi Trost✈️ ICML@atrost3122·
Nested models let you train a whole family of submodels at once. What if you could use them all at once, too? Block triangular weights enable this structure. It gives us token-adaptive routing, self-speculative decoding, and more. Introducing: Fully Nested Transformers (1/9)
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Keşfet

@fredsala @elonmusk @BarackObama @taylorswift13 @cristiano @BillGates @NASA @nikifrancismediavine