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cs.LG2026
Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization
Xiaoyuan Cheng, Wenxuan Yuan, Zhancun Mu +5
Model-based reinforcement learning (RL) can be effectively supported at scale through the use of world models. However, in practice, scaling such approaches remains fundamentally l…
cs.LG2026
Interdomain Attention: Beyond Token-Level Key-Value Memory
Naoki Kiyohara, Harrison Bo Hua Zhu, Riccardo El Hassanin +4
Softmax attention-based transformers and recurrent memory-based models (e.g., state space models (SSMs)) form the foundation of modern sequence models. Hybrid architectures aim to…