4 papers · 1 filter
GUPO: Gradient Uncertainty-aware Policy Optimization for Post-Training Large Language Models
Peizheng Guo, Jianqi Zhang, Xingyu Zhang +4
Group Relative Policy Optimization (GRPO) has become a widely used approach for post-training Large Language Models (LLMs) for reasoning. In GRPO, the group gradients induced by di…
Towards Generalizable Reasoning: Group Causal Counterfactual Policy Optimization for LLM Reasoning
Jingyao Wang, Peizheng Guo, Wenwen Qiang +4
Large language models (LLMs) excel at complex tasks with advances in reasoning capabilities. However, existing reward mechanisms remain tightly coupled to final correctness and pay…
Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration
Huijie Guo, Jingyao Wang, Peizheng Guo +3
In this paper, we explore the transferability of SSL by addressing two central questions: (i) what is the representation transferability of SSL, and (ii) how can we effectively mod…
Rethinking Multi-Modal Learning from Gradient Uncertainty
Peizheng Guo, Jingyao Wang, Wenwen Qiang +3
Multi-Modal Learning (MML) integrates information from diverse modalities to improve predictive accuracy. While existing optimization strategies have made significant strides by mi…