10 papers
RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models
Weijia Liufu, Xiaoyu Guo, Ruiyi Chen +16
Vision-Language-Action (VLA) models remain brittle in long-horizon, contact-rich manipulation because success-only imitation provides little supervision for execution drift, while…
Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI
Kun Xiang, Terry Jingchen Zhang, Yinya Huang +13
The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics rea…
EchoVLA: Robotic Vision-Language-Action Model with Synergistic Declarative Memory for Mobile Manipulation
Min Lin, Xiwen Liang, Bingqian Lin +13
Recent progress in Vision-Language-Action (VLA) models has enabled embodied agents to interpret multimodal instructions and perform complex tasks. However, existing VLAs are mostly…
RADAR: Revealing Asymmetric Development of Abilities in MLLM Pre-training
Yunshuang Nie, Bingqian Lin, Minzhe Niu +7
Pre-trained Multi-modal Large Language Models (MLLMs) provide a knowledge-rich foundation for post-training by leveraging their inherent perception and reasoning capabilities to so…
PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly
Liang Ma, Jiajun Wen, Min Lin +12
While vision-language models (VLMs) have demonstrated promising capabilities in reasoning and planning for embodied agents, their ability to comprehend physical phenomena, particul…
Unseen from Seen: Rewriting Observation-Instruction Using Foundation Models for Augmenting Vision-Language Navigation
Ziming Wei, Bingqian Lin, Yunshuang Nie +4
Data scarcity is a long-standing challenge in the Vision-Language Navigation (VLN) field, which extremely hinders the generalization of agents to unseen environments. Previous work…