5 papers
Nucleus Speculative Decoding: Plausibility-Aware Verification Beyond Exact Distribution
Shuhao Li, Fanghua Ye, Wanyu Lin +2
Speculative decoding (SD) accelerates autoregressive generation by letting a lightweight draft model propose tokens that a target model verifies in parallel. However, its standard…
On-Policy Supervised Fine-Tuning for Efficient Reasoning
Anhao Zhao, Ziyang Chen, Junlong Tong +6
Large reasoning models (LRMs) are commonly trained with reinforcement learning (RL) to explore long chain-of-thought reasoning, achieving strong performance at high computational c…
From LLMs to LRMs: Rethinking Pruning for Reasoning-Centric Models
Longwei Ding, Anhao Zhao, Fanghua Ye +2
Large language models (LLMs) are increasingly costly to deploy, motivating extensive research on model pruning. However, most existing studies focus on instruction-following LLMs,…
SkipGPT: Dynamic Layer Pruning Reinvented with Token Awareness and Module Decoupling
Anhao Zhao, Fanghua Ye, Yingqi Fan +4
Large language models (LLMs) achieve remarkable performance across tasks but incur substantial computational costs due to their deep, multi-layered architectures. Layer pruning has…
Unveiling In-Context Learning: A Coordinate System to Understand Its Working Mechanism
Anhao Zhao, Fanghua Ye, Jinlan Fu +1
Large language models (LLMs) exhibit remarkable in-context learning (ICL) capabilities. However, the underlying working mechanism of ICL remains poorly understood. Recent research…