7 citations · 17 across the 13 of their papers we have counts for
14 papers
RynnBrain: Open Embodied Foundation Models
Ronghao Dang, Jiayan Guo, Bohan Hou +23
Despite rapid progress in multimodal foundation models, embodied intelligence community still lacks a unified, physically grounded foundation model that integrates perception, reas…
RynnVLA-002: A Unified Vision-Language-Action and World Model
Jun Cen, Siteng Huang, Yuqian Yuan +11
We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…
PixelRefer: A Unified Framework for Spatio-Temporal Object Referring with Arbitrary Granularity
Yuqian Yuan, Wenqiao Zhang, Xin Li +6
Multimodal large language models (MLLMs) have demonstrated strong general-purpose capabilities in open-world visual comprehension. However, most existing MLLMs primarily focus on h…
Fast Thinking for Large Language Models
Haoyu Zheng, Zhuonan Wang, Yuqian Yuan +7
Reasoning-oriented Large Language Models (LLMs) often rely on generating explicit tokens step by step, and their effectiveness typically hinges on large-scale supervised fine-tunin…
RynnEC: Bringing MLLMs into Embodied World
Ronghao Dang, Yuqian Yuan, Yunxuan Mao +6
We introduce RynnEC, a video multimodal large language model designed for embodied cognition. Built upon a general-purpose vision-language foundation model, RynnEC incorporates a r…
EOC-Bench: Can MLLMs Identify, Recall, and Forecast Objects in an Egocentric World?
Yuqian Yuan, Ronghao Dang, Long Li +8
The emergence of multimodal large language models (MLLMs) has driven breakthroughs in egocentric vision applications. These applications necessitate persistent, context-aware under…
HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation
Tianwei Lin, Wenqiao Zhang, Sijing Li +12
We present HealthGPT, a powerful Medical Large Vision-Language Model (Med-LVLM) that integrates medical visual comprehension and generation capabilities within a unified autoregres…
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
Boqiang Zhang, Kehan Li, Zesen Cheng +12
In this paper, we propose VideoLLaMA3, a more advanced multimodal foundation model for image and video understanding. The core design philosophy of VideoLLaMA3 is vision-centric. T…
ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition Benchmark
Ronghao Dang, Yuqian Yuan, Wenqi Zhang +7
The enhancement of generalization in robots by large vision-language models (LVLMs) is increasingly evident. Therefore, the embodied cognitive abilities of LVLMs based on egocentri…
VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM
Yuqian Yuan, Hang Zhang, Wentong Li +9
Video Large Language Models (Video LLMs) have recently exhibited remarkable capabilities in general video understanding. However, they mainly focus on holistic comprehension and st…
Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents
Long Li, Weiwen Xu, Jiayan Guo +11
Effective research ideation is a critical step for scientific research. However, the exponential increase in scientific literature makes it challenging for researchers to stay curr…
TokenPacker: Efficient Visual Projector for Multimodal LLM
Wentong Li, Yuqian Yuan, Jian Liu +5
The visual projector serves as an essential bridge between the visual encoder and the Large Language Model (LLM) in a Multimodal LLM (MLLM). Typically, MLLMs adopt a simple MLP to…
Osprey: Pixel Understanding with Visual Instruction Tuning
Yuqian Yuan, Wentong Li, Jian Liu +5
Multimodal large language models (MLLMs) have recently achieved impressive general-purpose vision-language capabilities through visual instruction tuning. However, current MLLMs pr…
Label-efficient Segmentation via Affinity Propagation
Wentong Li, Yuqian Yuan, Song Wang +5
Weakly-supervised segmentation with label-efficient sparse annotations has attracted increasing research attention to reduce the cost of laborious pixel-wise labeling process, whil…