3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
BASIS: Batchwise Advantage Estimation from Single-Rollout Information Sharing for LLM Reasoning
Shijin Gong, Erhan Xu, Kai Ye +3
Reinforcement learning with verifiable rewards has become a standard recipe for improving the reasoning abilities of large language models. Existing algorithms face a tradeoff betw…
Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning
Shijin Gong, Kai Ye, Jin Zhu +3
Recent advances in large language models (LLMs) have increasingly relied on reinforcement learning (RL) to improve their reasoning capabilities. Three types of approaches have been…
Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic
Hongyi Zhou, Kai Ye, Erhan Xu +4
Group relative policy optimization (GRPO), a core methodological component of DeepSeekMath and DeepSeek-R1, has emerged as a cornerstone for scaling reasoning capabilities of large…
ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting
Hengyu Ye, Jiadong Chen, Shijin Gong +4
The intricate nature of time series data analysis benefits greatly from the distinct advantages offered by time and frequency domain representations. While the time domain is super…