26 citations · 38 across the 13 of their papers we have counts for
5 papers · 1 filter
Human-Level Accuracy, Non-Human Strategies: Revealing Model-Human Divergence in Video Physical Reasoning
Fanhong Li, Shurui Zheng, Zi Yin +3
Video foundation models now reach human-level accuracy on physical-reasoning benchmarks, yet such tasks require predicting unobserved physical outcomes. Do these models perform hum…
SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models
Cheng Yin, Wang Xu, Junpeng Yang +8
Long-horizon manipulation is partially observable: the information needed to choose the next action may appear only in observations from minutes earlier. Existing memory mechanisms…
Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction
Chaoqun He, Mingyang Xiang, Yingjing Xu +5
Real-time duplex interaction is essential for multimodal AI systems operating in real-world scenarios, where models must continuously process streaming inputs and respond at approp…
MiniCPM-V: A GPT-4V Level MLLM on Your Phone
Yuan Yao, Tianyu Yu, Ao Zhang +20
The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally reshaped the landscape of AI research and industry, shedding light on a promising path toward the nex…
LLaVA-UHD: an LMM Perceiving Any Aspect Ratio and High-Resolution Images
Ruyi Xu, Yuan Yao, Zonghao Guo +7
Visual encoding constitutes the basis of large multimodal models (LMMs) in understanding the visual world. Conventional LMMs process images in fixed sizes and limited resolutions,…