3 papers
cs.LG2025
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
Yang Zhou, Sunzhu Li, Shunyu Liu +11
Recent advances in Large Language Models (LLMs) have underscored the potential of Reinforcement Learning (RL) to facilitate the emergence of reasoning capabilities. Despite the enc…
cs.SI2024
Disentangled Condensation for Large-scale Graphs
Zhenbang Xiao, Yu Wang, Shunyu Liu +4
Graph condensation has emerged as an intriguing technique to save the expensive training costs of Graph Neural Networks (GNNs) by substituting a condensed small graph with the orig…
cs.LG2021
Up to 100 Faster Data-free Knowledge Distillation
Gongfan Fang, Kanya Mo, Xinchao Wang +4
Data-free knowledge distillation (DFKD) has recently been attracting increasing attention from research communities, attributed to its capability to compress a model only using syn…