11 papers
MIND-V: Hierarchical World Model for Long-Horizon Robotic Manipulation with RL-based Physical Alignment
Ruicheng Zhang, Mingyang Zhang, Jun Zhou +6
Scalable embodied intelligence is constrained by the scarcity of diverse, long-horizon robotic manipulation data. Existing video world models in this domain are limited to synthesi…
Learning Visual Spatial Planning from Symbolic State via Modality-Gap-Aware Self-Distillation
Haocheng Luo, Jiahui Liu, Ruicheng Zhang +8
While Vision-Language Models excel at general multimodal understanding, they still struggle with visual spatial planning. We attribute this limitation to a perception--reasoning mo…
Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling
Gongye Liu, Bo Yang, Yida Zhi +8
Preference optimization for diffusion and flow-matching models relies on reward functions that are both discriminatively robust and computationally efficient. Vision-Language Model…
EponaV2: Driving World Model with Comprehensive Future Reasoning
Jiawei Xu, Zhizhou Zhong, Zhijian Shu +8
Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving relies heavily on expensive man…
KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration
Ruicheng Zhang, Kaixi Cong, Jun Zhou +5
Aligning streaming autoregressive (AR) video generators with human preferences is challenging. Existing reinforcement learning methods predominantly rely on noise-based exploration…
Forcing-KV: Hybrid KV Cache Compression for Efficient Autoregressive Video Diffusion Models
Yicheng Ji, Zhizhou Zhong, Jun Zhang +7
Autoregressive (AR) video diffusion models adopt a streaming generation framework, enabling long-horizon video generation with real-time responsiveness, as exemplified by the Self…