activity
20182024
most citedLLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

119 citations · 558 across the 30 of their papers we have counts for

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32 papers · 1 filter

cs.CV20241 cited

Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers

Peng Gao, Le Zhuo, Dongyang Liu +17

Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lac…

cs.CV2024

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Renrui Zhang, Dongzhi Jiang, Yichi Zhang +8

The remarkable progress of Multi-modal Large Language Models (MLLMs) has garnered unparalleled attention, due to their superior performance in visual contexts. However, their capab…

cs.CV2024

SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models

Dongyang Liu, Renrui Zhang, Longtian Qiu +16

We propose SPHINX-X, an extensive Multimodality Large Language Model (MLLM) series developed upon SPHINX. To improve the architecture and training efficiency, we modify the SPHINX…

cs.CV202325 cited

SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

Ziyi Lin, Chris Liu, Renrui Zhang +13

We present SPHINX, a versatile multi-modal large language model (MLLM) with a joint mixing of model weights, tuning tasks, and visual embeddings. First, for stronger vision-languag…

cs.CV20236 cited

Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

Ziyu Guo, Renrui Zhang, Xiangyang Zhu +8

We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image, language, audio, and video. Guided by ImageBind, we construct a joint embedding space betwee…

cs.CV202320 cited

LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models

Peng Xu, Wenqi Shao, Kaipeng Zhang +7

Large Vision-Language Models (LVLMs) have recently played a dominant role in multimodal vision-language learning. Despite the great success, it lacks a holistic evaluation of their…