12 citations · 22 across the 16 of their papers we have counts for
6 papers · 1 filter
On the Plasticity and Stability for Post-Training Large Language Models
Wenwen Qiang, Ziyin Gu, Jiahuan Zhou +4
Training stability remains a critical bottleneck for Group Relative Policy Optimization (GRPO), often manifesting as a trade-off between reasoning plasticity and general capability…
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…
Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs
Jingyao Wang, Wenwen Qiang, Zeen Song +2
Large language models (LLMs) excel at complex tasks thanks to advances in their reasoning abilities. However, existing methods overlook the trade-off between reasoning effectivenes…
Neuromodulated Meta-Learning
Jingyao Wang, Huijie Guo, Wenwen Qiang +4
Humans excel at adapting perceptions and actions to diverse environments, enabling efficient interaction with the external world. This adaptive capability relies on the biological…
Towards Task Sampler Learning for Meta-Learning
Jingyao Wang, Wenwen Qiang, Xingzhe Su +3
Meta-learning aims to learn general knowledge with diverse training tasks conducted from limited data, and then transfer it to new tasks. It is commonly believed that increasing ta…
MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning
Jiangmeng Li, Wenwen Qiang, Yanan Zhang +4
As a successful approach to self-supervised learning, contrastive learning aims to learn invariant information shared among distortions of the input sample. While contrastive learn…