25 citations · 31 across the 4 of their papers we have counts for
4 papers
MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
Renrui Zhang, Xinyu Wei, Dongzhi Jiang +11
The mathematical capabilities of Multi-modal Large Language Models (MLLMs) remain under-explored with three areas to be improved: visual encoding of math diagrams, diagram-language…
MR-MLLM: Mutual Reinforcement of Multimodal Comprehension and Vision Perception
Guanqun Wang, Xinyu Wei, Jiaming Liu +5
In recent years, multimodal large language models (MLLMs) have shown remarkable capabilities in tasks like visual question answering and common sense reasoning, while visual percep…
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…
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…