3 papers
cs.CV2025
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…
cs.CV2025
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…
cs.CV2025
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…