273 citations · 1.4k across the 55 of their papers we have counts for
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cs.AI2026
Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?
Ming Zhong, Stacy Li, Nicholas Carlini +1
Frontier coding agents are increasingly framed as end-to-end automated researchers, and ML for science offers a demanding test of that promise: improving a scientific model often r…
cs.AI2025
Extracting alignment data in open models
Federico Barbero, Xiangming Gu, Christopher A. Choquette-Choo +6
In this work, we show that it is possible to extract significant amounts of alignment training data from a post-trained model -- useful to steer the model to improve certain capabi…