6 papers
See, Plan, Rewind: Progress-Aware Vision-Language-Action Models for Robust Robotic Manipulation
Tingjun Dai, Mingfei Han, Tingwen Du +6
Measurement of task progress through explicit, actionable milestones is critical for robust robotic manipulation. This progress awareness enables a model to ground its current task…
SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation
Longtao Jiang, Jianmin Bao, Zhendong Wang +4
Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-scale image generation. We i…
Beyond Dense Futures: World Models as Structured Planners for Robotic Manipulation
Minghao Jin, Mozheng Liao, Mingfei Han +2
Recent world-model-based Vision-Language-Action (VLA) architectures have improved robotic manipulation through predictive visual foresight. However, dense future prediction introdu…
Efficient Training for Human Video Generation with Entropy-Guided Prioritized Progressive Learning
Changlin Li, Jiawei Zhang, Shuhao Liu +4
Human video generation has advanced rapidly with the development of diffusion models, but the high computational cost and substantial memory consumption associated with training th…
Which Layer Causes Distribution Deviation? Entropy-Guided Adaptive Pruning for Diffusion and Flow Models
Changlin Li, Jiawei Zhang, Zeyi Shi +3
Large-scale vision generative models, including diffusion and flow models, have demonstrated remarkable performance in visual generation tasks. However, transferring these pre-trai…
CoNav: Collaborative Cross-Modal Reasoning for Embodied Navigation
Haihong Hao, Mingfei Han, Changlin Li +2
Embodied navigation demands comprehensive scene understanding and precise spatial reasoning. While image-text models excel at interpreting pixel-level color and lighting cues, 3D-t…