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20232026
most citedLMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

32 citations · 40 across the 24 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024★ 1 cited

Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models

Yuhao Dong, Zuyan Liu, Hai-Long Sun +4

Large Language Models (LLMs) demonstrate enhanced capabilities and reliability by reasoning more, evolving from Chain-of-Thought prompting to product-level solutions like OpenAI o1…

cs.CV2024★ 1 cited

Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution

Zuyan Liu, Yuhao Dong, Ziwei Liu +3

Visual data comes in various forms, ranging from small icons of just a few pixels to long videos spanning hours. Existing multi-modal LLMs usually standardize these diverse visual…

cs.CV2024★ 1 cited

3DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusion

Zhaoxi Chen, Jiaxiang Tang, Yuhao Dong +10

The increasing demand for high-quality 3D assets across various industries necessitates efficient and automated 3D content creation. Despite recent advancements in 3D generative mo…

cs.CV2024★ 1 cited

Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model

Benlin Liu, Yuhao Dong, Yiqin Wang +6

Multimodal language models (MLLMs) are increasingly being applied in real-world environments, necessitating their ability to interpret 3D spaces and comprehend temporal dynamics. C…

cs.CV2024

Efficient Inference of Vision Instruction-Following Models with Elastic Cache

Zuyan Liu, Benlin Liu, Jiahui Wang +5

In the field of instruction-following large vision-language models (LVLMs), the efficient deployment of these models faces challenges, notably due to the high memory demands of the…

cs.CL2024★ 32 cited

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Kaichen Zhang, Bo Li, Peiyuan Zhang +8

The advances of large foundation models necessitate wide-coverage, low-cost, and zero-contamination benchmarks. Despite continuous exploration of language model evaluations, compre…

cs.CV2024★ 1 cited

Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models

Zuyan Liu, Yuhao Dong, Yongming Rao +2

In the realm of vision-language understanding, the proficiency of models in interpreting and reasoning over visual content has become a cornerstone for numerous applications. Howev…