From the 1 of 9 linked papers with an AI index.
5 papers · 1 filter
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…
ContentV: Efficient Training of Video Generation Models with Limited Compute
Wenfeng Lin, Renjie Chen, Boyuan Liu +10
Recent advances in video generation demand increasingly efficient training recipes to mitigate escalating computational costs. In this report, we present ContentV, an 8B-parameter…
H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding
Qi Wu, Quanlong Zheng, Yanhao Zhang +8
With the rapid development of multimodal models, the demand for assessing video understanding capabilities has been steadily increasing. However, existing benchmarks for evaluating…
NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation
Jiazhao Zhang, Kunyu Wang, Rongtao Xu +6
Vision-and-language navigation (VLN) stands as a key research problem of Embodied AI, aiming at enabling agents to navigate in unseen environments following linguistic instructions…