9 papers
RayViT: Ray-Conditioned Visual Representations for Viewpoint-Robust Imitation Learning
Qian Wang, Longrui Chen, Peiran Sun +8
Visual imitation learning enables robots to acquire visuomotor skills directly from images, yet RGB observations lack explicit geometric cues, making learned policies brittle to ca…
Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
Zhanzhi Lou, Hui Chen, Yibo Li +2
The paper introduces Meta-TTL, a bi‑level optimization framework that learns adaptation policies for test‑time learning in language agents, using evolutionary search to improve per…
Artificial Foveated Perception for Mitigating Shortcut Learning in Robotic Foundation Models
Xiatao Sun, Yuan Zhuang, Mateo Sanchez Lopez Negrete +9
Robotic foundation models have recently made substantial progress in multi-task capability, cross-embodiment transfer, and language-conditioned control. Yet robust deployment acros…
WALL-WM: Carving World Action Modeling at the Event Joints
Shalfun Li, Victor Yao, Charles Yang +28
WALL-WM is a World Action Model that shifts video-action learning from chunk-centric optimization to event-grounded Vision-Language-Action pretraining, using semantically coherent…
Wall-OSS-0.5 Technical Report
Ryan Yu, Pushi Zhang, Starrick Liu +24
Large-scale Vision-Language-Action (VLA) pretraining is increasingly adopted as the foundation for robot policies, yet the evidence for pretrained VLAs is almost invariably reporte…
MMDG-Bench: A Benchmark for Multimodal Domain Generalization
Qianshan Zhan, Qian Wang, Da Li +2
Multi-modal Domain Generalization (MMDG) seeks to leverage complementary modalities to enhance model robustness on unseen domains. Despite extensive progress in Multi-modal Learnin…