4 citations · 6 across the 18 of their papers we have counts for
6 papers · 1 filter
UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models
Xidong Zhang, Yichi Zhang, Jiaxin Shi +5
Vision-language-action (VLA) models have achieved strong performance in many robotic manipulation tasks, yet remain limited in contact-rich dexterous manipulation. To overcome this…
Variational Learning for Insertion-based Generation
Yangtian Zhang, Zhe Wang, Arthur Gretton +4
Non-monotonic sequence generation methods, such as masked diffusion models, provide a flexible alternative to left-to-right autoregressive modeling by allowing tokens to be generat…
3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training
Jiaxin Shi, Xidong Zhang, Fucai Zhu +3
We propose a 3D-thinking-guided co-training framework that enables vision-language-action (VLA) models to perform 3D spatial reasoning implicitly during action prediction. Our core…
RealCam: Real-Time Novel-View Video Generation with Interactive Camera Control
Youcan Xu, Jiaxin Shi, Zhen Wang +5
Camera-controlled video-to-video (V2V) generation enables dynamic viewpoint synthesis from monocular footage, holding immense potential for interactive filmmaking and live broadcas…
DiT as Real-Time Rerenderer: Streaming Video Stylization with Autoregressive Diffusion Transformer
Hengye Lyu, Zisu Li, Yue Hong +4
Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization holds important research valu…
Generative Frontiers: Why Evaluation Matters for Diffusion Language Models
Patrick Pynadath, Jiaxin Shi, Ruqi Zhang
Diffusion language models have seen exciting recent progress, offering far more flexibility in generative trajectories than autoregressive models. This flexibility has motivated a…