4 papers
PA1-OPD: One-Step Prefix-Augmented On-Policy Distillation for Language Model Pretraining
Zhenhe Wu, Jian Yang, Yaping Jin +3
Knowledge distillation (KD) improves language-model pretraining by matching teacher distributions at corpus prefixes, but provides no direct supervision at contexts induced by stud…
Cache-Aware Joint Router Adaptation for Memory-Efficient MoE Inference
Zhenhe Wu, Yaping Jin, Qinghua Xing +6
Mixture-of-Experts (MoE) models activate few experts per token, yet their full expert sets can exceed GPU memory and require repeated weight transfers during decoding. We formulate…
SpecBlock: Block-Iterative Speculative Decoding with Dynamic Tree Drafting
Weijie Shi, Qiang Xu, Fan Deng +9
Speculative decoding accelerates LLM inference by drafting a tree of candidate continuations and verifying it in one target forward. Existing drafters fall into two camps with oppo…
A Survey on Progress in LLM Alignment from the Perspective of Reward Design
Miaomiao Ji, Yanqiu Wu, Zhibin Wu +4
Reward design plays a pivotal role in aligning large language models (LLMs) with human values, serving as the bridge between feedback signals and model optimization. This survey pr…