Nicholas Lourie
nicholaslourie.bsky.social
Nicholas Lourie
@nicholaslourie.bsky.social
Better empirical methods for deep learning & NLP. PhD at NYU. Advised by He He and @kyunghyuncho.bsky.social. Prev: @ai2.bsky.social.

I build things. 🤖
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📄🔈✨ Deep learning is an empirical science, but we rely on basic empirical methods. What might a better foundation—a simple theory—for empirical work look like?

@kyunghyuncho.bsky.social, He He, and I move towards one in "Hyperparameter Loss Surfaces Are Simple Near their Optima" at #COLM2025!

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📄🔈✨ Deep learning is an empirical science, but we rely on basic empirical methods. What might a better foundation—a simple theory—for empirical work look like?

@kyunghyuncho.bsky.social, He He, and I move towards one in "Hyperparameter Loss Surfaces Are Simple Near their Optima" at #COLM2025!

🧵1/9
October 8, 2025 at 8:14 PM
Reposted by Nicholas Lourie
Can we predict emergent capabilities in GPT-N+1🌌 using only GPT-N model checkpoints, which have random performance on the task?

We propose a method for doing exactly this in our paper “Predicting Emergent Capabilities by Finetuning”🧵
November 26, 2024 at 10:37 PM