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Pete Shaw

@ptshaw.bsky.social
1.6K followers 356 following 9 posts

Research Scientist at Google DeepMind. Mostly work on ML, NLP, and BioML. Based in Seattle. ptshaw.com

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Pete Shaw @ptshaw.bsky.social · 01/10/2025
w/ James Cohan, @jacobeisenstein.bsky.social, and Kristina Toutanova Paper link: arxiv.org/abs/2509.22445
arxiv.org
Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
The Minimum Description Length (MDL) principle offers a formal framework for applying Occam's razor in machine learning. However, its application to neural networks such as Transformers is challenging...
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Pete Shaw @ptshaw.bsky.social · 01/10/2025
We hope this work adds some conceptual clarity around how Kolmogorov complexity relates to neural networks, and provides a path towards identifying new complexity measures that enable greater compression and generalization.
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Pete Shaw @ptshaw.bsky.social · 01/10/2025
We prove that asymptotically optimal objectives exist for Transformers, building on a new demonstration of their computational universality. We also highlight potential challenges related to effectively optimizing such objectives.
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Pete Shaw @ptshaw.bsky.social · 01/10/2025
To address this question, we define the notion of asymptotically optimal description length objectives. We establish that a minimizer of such an objective achieves optimal compression, for any dataset, up to an additive constant, in the limit as model resource bounds increase.
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Pete Shaw @ptshaw.bsky.social · 01/10/2025
The Kolmogorov complexity of an object is the length of the shortest program that prints that object. Combining Kolmogorov complexity with the MDL principle provides an elegant foundation for formalizing Occam’s razor. But how can these ideas be applied to neural networks?
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Pete Shaw @ptshaw.bsky.social · 01/10/2025
Excited to share a new paper that aims to narrow the conceptual gap between the idealized notion of Kolmogorov complexity and practical complexity measures for neural networks.
Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
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Reposted by Pete Shaw
Ahmad Beirami @abeirami.bsky.social · 01/01/2025
Excited to share 𝐈𝐧𝐟𝐀𝐥𝐢𝐠𝐧! Alignment optimization objective implicitly assumes 𝘴𝘢𝘮𝘱𝘭𝘪𝘯𝘨 from the resulting aligned model. But we are increasingly using different and sometimes sophisticated inference-time compute algorithms. How to resolve this discrepancy?🧵
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins, Adrian Hutter, Jong Lee, Chirag Nagpal, Flavien Prost, Aradhana Sinha, Ananda Theertha Suresh, Ahmad Beirami
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Pete Shaw @ptshaw.bsky.social · 09/12/2024
I'll be at NeurIPS this week. Please reach out if you would like to chat!
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Reposted by Pete Shaw
Marc Lanctot @sharky6000.bsky.social · 28/10/2024
New starter pack! go.bsky.app/GZ4hZzu
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Reposted by Pete Shaw
Kevin K. Yang 楊凱筌 @kevinkaichuang.bsky.social · 18/11/2024
Two BioML starter packs now: Pack 1: go.bsky.app/2VWBcCd Pack 2: go.bsky.app/Bw84Hmc DM if you want to be included (or nominate people who should be!)
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Pete Shaw @ptshaw.bsky.social · 19/11/2024
Hi Marc, thanks for putting this together, mind adding me?
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Reposted by Pete Shaw
Kuzman Ganchev @ganchev.bsky.social · 11/11/2024
Wanted to share that Varun Godbole recently released a prompting playbook. The title says prompt tuning, but this is text prompts, not soft prompts. github.com/varungodbole...
github.com
GitHub - varungodbole/prompt-tuning-playbook: A playbook for effectively prompting post-trained LLMs
A playbook for effectively prompting post-trained LLMs - varungodbole/prompt-tuning-playbook
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Reposted by Pete Shaw
Maike Osborne @maosbot.bsky.social · 09/11/2024
New here? Interested in AI/ML? Check out these great starter packs! AI: go.bsky.app/SipA7it RL: go.bsky.app/3WPHcHg Women in AI: go.bsky.app/LaGDpqg NLP: go.bsky.app/SngwGeS AI and news: go.bsky.app/5sFqVNS You can also search all starter packs here: blueskydirectory.com/starter-pack...
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Pete Shaw @ptshaw.bsky.social · 11/11/2024
Getting set up on Bluesky today!
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Reposted by Pete Shaw
Jacob Eisenstein is at CoLM 🌉 @jacobeisenstein.bsky.social · 24/10/2024
I’m pretty excited about this one! ALTA is A Language for Transformer Analysis. Because ALTA programs can be compiled to transformer weights, it provides constructive proofs of transformer expressivity. It also offers new analytic tools for *learnability*. arxiv.org/abs/2410.18077
arxiv.org
ALTA: Compiler-Based Analysis of Transformers
We propose a new programming language called ALTA and a compiler that can map ALTA programs to Transformer weights. ALTA is inspired by RASP, a language proposed by Weiss et al. (2021), and Tracr (Lin...
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