3 papers
cs.CL2026
Improving Reasoning Ability via Asynchronous On-Policy Self-Distillation under Positive Rollouts
Mingwei Xu, Hao Fang
Distillation and reinforcement learning through verifiable rewards (RLVR) have achieved progress in enhancing the reasoning ability of large language models (LLMs). However, we not…
cs.LG2025
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation
Xiaofeng Cao, Mingwei Xu, Xin Yu +8
Learning with high-resource data has demonstrated substantial success in artificial intelligence (AI); however, the costs associated with data annotation and model training remain…
cs.LG2023
Aggregation Weighting of Federated Learning via Generalization Bound Estimation
Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang +1
Federated Learning (FL) typically aggregates client model parameters using a weighting approach determined by sample proportions. However, this naive weighting method may lead to u…