2 citations · 3 across the 14 of their papers we have counts for
6 papers · 1 filter
Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs
Yunheng Li, Guohong Mu, Hao Li +4
Multimodal large language models (MLLMs) have become a prevailing paradigm for unified video perception. However, post-training on large multi-task datasets remains challenging, as…
Hy-Embodied-VLM-1.0: Efficient Physical-World Agents
Ziyi Wang, Xumin Yu, Yongming Rao +19
Building capable embodied agents requires not only multimodal perception and understanding, but also agentic capabilities for reasoning about actions, adapting to evolving situatio…
SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection
Chenxu Wang, Yuxuan Li, Yunheng Li +3
Existing language-image pre-training for remote sensing object detection is constrained by Monolithic Label Learning, which relies on exhaustively enumerating open-set categories v…
Rethinking Token-Level Policy Optimization for Multimodal Chain-of-Thought
Yunheng Li, Hangyi Kuang, Hengrui Zhang +4
Multimodal Chain-of-Thought (CoT) reasoning requires large vision-language models to construct reasoning trajectories that interleave perceptual grounding with multi-step inference…
Unifying Heterogeneous Multi-Modal Remote Sensing Detection Via Language-Pivoted Pretraining
Yuxuan Li, Yuming Chen, Yunheng Li +3
Heterogeneous multi-modal remote sensing object detection aims to accurately detect objects from diverse sensors (e.g., RGB, SAR, Infrared). Existing approaches largely adopt a lat…
Towards Universal Video MLLMs with Attribute-Structured and Quality-Verified Instructions
Yunheng Li, Hengrui Zhang, Meng-Hao Guo +5
Universal video understanding requires modeling fine-grained visual and audio information over time in diverse real-world scenarios. However, the performance of existing models is…