5 papers
Prune-Then-Plan: Step-Level Calibration for Stable Frontier Exploration in Embodied Question Answering
Noah Frahm, Prakrut Patel, Yue Zhang +3
Large vision-language models (VLMs) have improved embodied question answering (EQA) agents by providing strong semantic priors for open-vocabulary reasoning. However, when used dir…
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…
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…
SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts
Gengze Zhou, Yicong Hong, Zun Wang +3
The academic field of learning instruction-guided visual navigation can be generally categorized into high-level category-specific search and low-level language-guided navigation,…
Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
Zun Wang, Jialu Li, Yicong Hong +8
Creating high-quality data for training robust language-instructed agents is a long-lasting challenge in embodied AI. In this paper, we introduce a Self-Refining Data Flywheel (SRD…