Author

Adam Block

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#machine learning Preprint Oct 2026

LLM Evaluation is a Forecasting Problem

Standard procedure in machine learning is to randomly split train and test data, emulating IID draws from one underlying data distribution. In practice, models are trained on past data and deployed in the future, which may come from distinct distributions. In this paper, we find that web text is indeed highly non-stati...

R. Thomas, Adam Block, Micah Goldblum · 0 citations

Jun 2026

Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback

A noisy expert model is proposed to explain why OPD can outperform SFT when training language models from imperfect teachers, and it is proved that online interaction with the noisy expert via a novel variant of OPD enables polynomial dependence on the horizon in general.

V. Sriraman, Peihan Liu, Daniel Hsu et al. · arXiv.org · 0 citations