2 papers
cs.CL2026
Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models
Aiwei Liu, Cheng Shi, Chuhan Wu +44
Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining…
cs.LG2026
Scaling Learning-based AEB with Massive Unlabeled Data
Xiangyu Wang, Yang Zhan, Mengxiang Hao +9
This paper studies how to scale learning-based automatic emergency braking (AEB) with massive unlabeled fleet data under production constraints. Our approach is based on meta-feedb…