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Hands-on AutoResearch: Cracking OpenAI's Parameter Golf

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Session Description

Heard about autoresearch, or tried it a few times in playground settings? This hands-on tutorial teaches you how to use autoresearch on one of the most serious challenges in ML this year: OpenAI's Parameter Golf. The challenge: train the best language model that fits in just 16MB. We entered our autoresearch agent this past spring, and it outperformed the field of over 1,000 participants. You'll learn how we approached it, then get to do it yourself: kick off an autoresearch agent, watch it improve a tiny language model's training script, steer it when progress stalls, and visualize your results. You'll leave with a working autoresearch setup you can point at your own code. compute kindly sponsored by Modal!

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Hands-on AutoResearch: Cracking OpenAI's Parameter Golf ## Conference Context - Date/time: 2026-06-29 · 2:20pm-4:20pm - Track/room: Workshops Day 1 · Track 9 - Speaker(s): Zhengyao Jiang, Dixing Xu, Vayum Arora, Dhruv Srikanth - Session type/status: session · confirmed - Track: Workshops Day 1 - Room: Track 9 - Session type: session - Status: confirmed ## Session Description Heard about autoresearch, or tried it a few times in playground settings? This hands-on tutorial teaches you how to use autoresearch on one of the most serious challenges in ML this year: OpenAI's Parameter Golf. The challenge: train the best language model that fits in just 16MB. We entered our autoresearch agent this past spring, and it outperformed the field of over 1,000 participants.

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