2 papers
cs.LG2026
Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers
Atsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo
Length generalization is the ability of language models to maintain performance on inputs longer than those seen during pretraining. In this work, we introduce a simple yet powerfu…
cs.LG2024
Improved Active Learning via Dependent Leverage Score Sampling
Atsushi Shimizu, Xiaoou Cheng, Christopher Musco +1
We show how to obtain improved active learning methods in the agnostic (adversarial noise) setting by combining marginal leverage score sampling with non-independent sampling strat…