activity
20242026
most citedCambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

13 citations · 14 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

VULCAN: Tool-Augmented Multi Agents for Iterative 3D Object Arrangement

Zhengfei Kuang, Rui Lin, Long Zhao +3

Despite the remarkable progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, their application to complex 3D scene manipulation remains underexplored. I…

cs.LG2025

Image Diffusion Preview with Consistency Solver

Fu-Yun Wang, Hao Zhou, Liangzhe Yuan +8

The slow inference process of image diffusion models significantly degrades interactive user experiences. To address this, we introduce Diffusion Preview, a novel paradigm employin…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CV2025

BlenderFusion: 3D-Grounded Visual Editing and Generative Compositing

Jiacheng Chen, Ramin Mehran, Xuhui Jia +2

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compos…

cs.CV2024

Epsilon-VAE: Denoising as Visual Decoding

Long Zhao, Sanghyun Woo, Ziyu Wan +6

In generative modeling, tokenization simplifies complex data into compact, structured representations, creating a more efficient, learnable space. For high-dimensional visual data,…

cs.CV2024★ 13 cited

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Shengbang Tong, Ellis Brown, Penghao Wu +11

We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-centric approach. While stronger language models can enhance multimodal capabilities, the design…

cs.CV2024

SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting

Hoon Kim, Minje Jang, Wonjun Yoon +3

We introduce a co-designed approach for human portrait relighting that combines a physics-guided architecture with a pre-training framework. Drawing on the Cook-Torrance reflectanc…