activity
20192026
most citedKnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning

16 citations · 42 across the 18 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

MAny: Merge Anything for Multimodal Continual Instruction Tuning

Zijian Gao, Wangwang Jia, Xingxing Zhang +6

Multimodal Continual Instruction Tuning (MCIT) is essential for sequential task adaptation of Multimodal Large Language Models (MLLMs) but is severely restricted by catastrophic fo…

cs.LG2024

Optimistic Model Rollouts for Pessimistic Offline Policy Optimization

Yuanzhao Zhai, Yiying Li, Zijian Gao +5

Model-based offline reinforcement learning (RL) has made remarkable progress, offering a promising avenue for improving generalization with synthetic model rollouts. Existing works…

cs.LG2022★ 1 cited

Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning

Zijian Gao, Kele Xu, Yuanzhao Zhai +4

Under sparse extrinsic reward settings, reinforcement learning has remained challenging, despite surging interests in this field. Previous attempts suggest that intrinsic reward ca…

cs.LG2022★ 1 cited

Nuclear Norm Maximization Based Curiosity-Driven Learning

Chao Chen, Zijian Gao, Kele Xu +5

To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in…

cs.LG2019★ 5 cited

Random forest model identifies serve strength as a key predictor of tennis match outcome

Zijian Gao, Amanda Kowalczyk

Tennis is a popular sport worldwide, boasting millions of fans and numerous national and international tournaments. Like many sports, tennis has benefitted from the popularity of r…