Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
A Unified Framework for In-Context Learning with Causal and Masked Language Models
Chenrui Liu, Chuanlong Xie, Falong Tan +2
In-context learning (ICL) has emerged as a central capability of pretrained language models, yet its theoretical analysis has focused primarily on causal language models trained by…
cs.LG2024
Provable Contrastive Continual Learning
Yichen Wen, Zhiquan Tan, Kaipeng Zheng +2
Continual learning requires learning incremental tasks with dynamic data distributions. So far, it has been observed that employing a combination of contrastive loss and distillati…
cs.LG2024
Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion
Jiawei Li, Sitong Li, Shanshan Wang +3
Deploying machine learning in open environments presents the challenge of encountering diverse test inputs that differ significantly from the training data. These out-of-distributi…