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cs.CL2026
Recursive Language Models Generalize Out of Domain
Chenxiao Yang, Zhiyuan Li, David McAllester +1
We study when limiting what a language model can see improves learning. We compare standard CoT, the more general learner that reads the full trace, with recursive language models,…
cs.LG2026
Hierarchical Domain Generalization
Chenxiao Yang, Zhiyuan Li, Shai Ben-David +1
We study hierarchical domain generalization as a problem of extrapolation from finite observed regions to an entire instance space, replacing i.i.d. sampling with arbitrary domain…
stat.ML2026
Overfitting and Generalizing with (PAC) Bayesian Prediction in Noisy Binary Classification
Xiaohan Zhu, Mesrob I. Ohannessian, Nathan Srebro
We consider a PAC-Bayes type learning rule for binary classification, balancing the training error of a randomized ''posterior'' predictor with its KL divergence to a pre-specified…