10 papers
Bridging the Discrete-Continuous Gap: Unified Multimodal Generation via Coupled Manifold Discrete Absorbing Diffusion
Yuanfeng Xu, Yuhao Chen, Liang Lin +1
The bifurcation of generative modeling into autoregressive approaches for discrete data (text) and diffusion approaches for continuous data (images) hinders the development of trul…
ACD: Direct Conditional Control for Video Diffusion Models via Attention Supervision
Weiqi Li, Zehao Zhang, Liang Lin +1
Controllability is a fundamental requirement in video synthesis, where accurate alignment with conditioning signals is essential. Existing classifier-free guidance methods typicall…
Human-Centric Open-Future Task Discovery: Formulation, Benchmark, and Scalable Tree-Based Search
Zijian Song, Xiaoxin Lin, Tao Pu +3
Recent progress in robotics and embodied AI is largely driven by Large Multimodal Models (LMMs). However, a key challenge remains underexplored: how can we advance LMMs to discover…
In-Situ Tweedie Discrete Diffusion Models
Xiao Li, Jiaqi Zhang, Shuxiang Zhang +3
While diffusion models excel at generating continuous data such as images, adapting them to discrete tasks has relied on indirect approaches that either operate in continuous embed…
UML-CoT: Structured Reasoning and Planning with Unified Modeling Language for Robotic Room Cleaning
Hongyu Chen, Guangrun Wang
Chain-of-Thought (CoT) prompting improves reasoning in large language models (LLMs), but its reliance on unstructured text limits interpretability and executability in embodied tas…
Physical Autoregressive Model for Robotic Manipulation without Action Pretraining
Zijian Song, Sihan Qin, Tianshui Chen +2
The scarcity of manipulation data has motivated the use of pretrained large models from other modalities in robotics. In this work, we build upon autoregressive video generation mo…