2 papers
cs.LG2026
Control-Diverse Reinforcement Fine-Tuning: Decoupling the Shared Control Bottleneck of RL Post-Training
Binwen Tan, Jingchao Wang, Dengzhe Hou +6
Reinforcement learning post-training unlocks complex reasoning in LLMs. Yet benchmark scores reveal only whether a model improved, not what changed inside it, nor how it splits fin…
cs.CV2026
MWorld: A Multi-view Multimodal Driving World Model for Interactive Object Manipulation and Minute-long Streaming
Ke Cheng, Hanqiao Ye, Lei Shi +8
Driving-world generation has emerged as a core capability for scalable autonomous-driving simulation, yet existing methods remain limited in object-level controllability and long-h…