5 papers
Revisiting Generative Policies: A Simpler Reinforcement Learning Algorithmic Perspective
Jinouwen Zhang, Rongkun Xue, Yazhe Niu +4
Generative models, particularly diffusion models, have achieved remarkable success in density estimation for multimodal data, drawing significant interest from the reinforcement le…
Pretrained Reversible Generation as Unsupervised Visual Representation Learning
Rongkun Xue, Jinouwen Zhang, Yazhe Niu +4
Recent generative models based on score matching and flow matching have significantly advanced generation tasks, but their potential in discriminative tasks remains underexplored.…
PsyDI: Towards a Personalized and Progressively In-depth Chatbot for Psychological Measurements
Xueyan Li, Xinyan Chen, Yazhe Niu +2
In the field of psychology, traditional assessment methods, such as standardized scales, are frequently critiqued for their static nature, lack of personalization, and reduced part…
UniZero: Generalized and Efficient Planning with Scalable Latent World Models
Yuan Pu, Yazhe Niu, Zhenjie Yang +3
Learning predictive world models is crucial for enhancing the planning capabilities of reinforcement learning (RL) agents. Recently, MuZero-style algorithms, leveraging the value e…
ReZero: Boosting MCTS-based Algorithms by Backward-view and Entire-buffer Reanalyze
Chunyu Xuan, Yazhe Niu, Yuan Pu +3
Monte Carlo Tree Search (MCTS)-based algorithms, such as MuZero and its derivatives, have achieved widespread success in various decision-making domains. These algorithms employ th…