7 papers
VLN-MME: Diagnosing MLLMs as Language-guided Visual Navigation agents
Xunyi Zhao, Gengze Zhou, Qi Wu
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across a wide range of vision-language tasks. However, their performance as embodied agents, whic…
VLNVerse: A Benchmark for Vision-Language Navigation with Versatile, Embodied, Realistic Simulation and Evaluation
Sihao Lin, Zerui Li, Xunyi Zhao +10
Despite remarkable progress in Vision-Language Navigation (VLN), existing benchmarks remain confined to fixed, small-scale datasets with naive physical simulation. These shortcomin…
MMGR: Multi-Modal Generative Reasoning
Zefan Cai, Haoyi Qiu, Tianyi Ma +9
Video foundation models generate visually realistic and temporally coherent content, but their reliability as world simulators depends on whether they capture physical, logical, an…
Rethinking Training Dynamics in Scale-wise Autoregressive Generation
Gengze Zhou, Chongjian Ge, Hao Tan +2
Recent advances in autoregressive (AR) generative models have produced increasingly powerful systems for media synthesis. Among them, next-scale prediction has emerged as a popular…
Embodied Navigation Foundation Model
Jiazhao Zhang, Anqi Li, Yunpeng Qi +14
Navigation is a fundamental capability in embodied AI, representing the intelligence required to perceive and interact within physical environments following language instructions.…
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments
Zerui Li, Gengze Zhou, Haodong Hong +4
Vision-and-Language Navigation (VLN) empowers agents to associate time-sequenced visual observations with corresponding instructions to make sequential decisions. However, generali…