5 papers
Would you still call this Dax? Novel Visual References in VLMs and Humans
Ada Defne Tür, Gaurav Kamath, Joyce Chai +2
Vision-language models (VLMs), like human learners, are frequently exposed to new visual concepts, but how they map novel visual references to language after exposure remains large…
Fast Spatial Memory with Elastic Test-Time Training
Ziqiao Ma, Xueyang Yu, Haoyu Zhen +3
Large Chunk Test-Time Training (LaCT) has shown strong performance on long-context 3D reconstruction, but its fully plastic inference-time updates remain vulnerable to catastrophic…
Next-Embedding Prediction Makes Strong Vision Learners
Sihan Xu, Ziqiao Ma, Wenhao Chai +5
Inspired by the success of generative pretraining in natural language, we ask whether the same principles can yield strong self-supervised visual learners. Instead of training mode…
VEGGIE: Instructional Editing and Reasoning Video Concepts with Grounded Generation
Shoubin Yu, Difan Liu, Ziqiao Ma +5
Recent video diffusion models have enhanced video editing, but it remains challenging to handle instructional editing and diverse tasks (e.g., adding, removing, changing) within a…
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu +10
Can we scale 4D pretraining to learn general space-time representations that reconstruct an object from a few views at some times to any view at any time? We provide an affirmative…