2 papers
cs.CL2026
BLADE: Boundary-Expanded and Layer-Adaptive Dynamic Exit for Efficient LLM Reasoning
Keshu Fu, Keqin Peng, Jun Bai +6
Large language models often improve task performance by generating long reasoning traces, but the resulting computation is frequently wasted on redundant verification and revision.…
cs.LG2026
CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure
Boao Kong, Junzhu Liang, Yuxi Liu +2
Low-rank architectures have become increasingly important for efficient large language model (LLM) pre-training, providing substantial reductions in both parameter complexity and m…