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cs.LG2026
Antidistillation Fingerprinting
Yixuan Even Xu, John Kirchenbauer, Yash Savani +5
Model distillation enables efficient emulation of frontier large language models (LLMs), creating a need for robust mechanisms to detect when a third-party student model has traine…
cs.LG2025
Existing Large Language Model Unlearning Evaluations Are Inconclusive
Zhili Feng, Yixuan Even Xu, Alexander Robey +5
Machine unlearning aims to remove sensitive or undesired data from large language models. However, recent studies suggest that unlearning is often shallow, claiming that removed kn…
cs.LG2025
Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
Yixuan Even Xu, Yash Savani, Fei Fang +1
Reinforcement learning with verifiable rewards (RLVR) has emerged as the leading approach for enhancing reasoning capabilities in large language models. However, it faces a fundame…