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20172026
most citedObfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1.1k citations · 3k across the 8 of their papers we have counts for

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cs.LG2026

A Cheap Verifier is Good Enough: LLM Post-training is Robust to Erroneous Rewards

Andreas Plesner, Curtis Northcutt, Francisco Guzmán +1

When post-training large language models on tasks with semi-verifiable rewards, there are many factors (training steps, base model size, training order, data quality, verifier accu…

cs.LG2026

An Imperfect Verifier is Good Enough: Learning with Noisy Rewards

Andreas Plesner, Francisco Guzmán, Anish Athalye

Reinforcement Learning with Verifiable Rewards (RLVR) is widely used for post-training Large Language Models, but practical verifiers can make errors. We study how the rate and str…