4 papers
INFUSER: Influence-Guided Self-Evolution Improves Reasoning
Siyu Chen, Miao Lu, Beining Wu +7
Self-evolution offers a scalable path to stronger reasoning: a pretrained language model improves itself with only minimal external supervision. Yet existing methods either depend…
Provable Benefit of SignGD: A Minimal Model Under Heavy-Tailed Class Imbalance
Robin Yadav, Shuo Xie, Tianhao Wang +1
Adaptive and non-Euclidean optimizers often outperform Euclidean methods such as stochastic gradient descent (SGD) in language modeling by a large margin. Existing theory usually e…
A Tale of Two Geometries: Adaptive Optimizers and Non-Euclidean Descent
Shuo Xie, Tianhao Wang, Beining Wu +1
Adaptive optimizers can reduce to normalized steepest descent (NSD) when only adapting to the current gradient, suggesting a close connection between the two algorithmic families.…
Honesty over Accuracy: Trustworthy Language Models through Reinforced Hesitation
Mohamad Amin Mohamadi, Tianhao Wang, Zhiyuan Li
Modern language models fail a fundamental requirement of trustworthy intelligence: knowing when not to answer. Despite achieving impressive accuracy on benchmarks, these models pro…