most citedTactile DreamFusion: Exploiting Tactile Sensing for 3D Generation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Xiaomi MiMo-VL-Miloco Technical Report

Jiaze Li, Jingyang Chen, Yuxun Qu +9

We open-source MiMo-VL-Miloco-7B and its quantized variant MiMo-VL-Miloco-7B-GGUF, a pair of home-centric vision-language models that achieve strong performance on both home-scenar…

cs.CV2025

Part-X-MLLM: Part-aware 3D Multimodal Large Language Model

Chunshi Wang, Junliang Ye, Yunhan Yang +6

We introduce Part-X-MLLM, a native 3D multimodal large language model that unifies diverse 3D tasks by formulating them as programs in a structured, executable grammar. Given an RG…

cs.AI2025

Imagine in Space: Exploring the Frontier of Spatial Intelligence and Reasoning Efficiency in Vision Language Models

Xiaoxing Lian, Aidong Yang, Jun Zhu +2

Large language models (LLMs) and vision language models (VLMs), such as DeepSeek R1,OpenAI o3, and Gemini 2.5 Pro, have demonstrated remarkable reasoning capabilities across logica…

cs.RO2025

Prompt-to-Product: Generative Assembly via Bimanual Manipulation

Ruixuan Liu, Philip Huang, Ava Pun +8

Creating assembly products demands significant manual effort and expert knowledge in 1) designing the assembly and 2) constructing the product. This paper introduces Prompt-to-Prod…

cs.CV2025

Generating Physically Stable and Buildable Brick Structures from Text

Ava Pun, Kangle Deng, Ruixuan Liu +3

We introduce BrickGPT, the first approach for generating physically stable interconnecting brick assembly models from text prompts. To achieve this, we construct a large-scale, phy…

cs.CV2025

Efficient Autoregressive Shape Generation via Octree-Based Adaptive Tokenization

Kangle Deng, Hsueh-Ti Derek Liu, Yiheng Zhu +7

Many 3D generative models rely on variational autoencoders (VAEs) to learn compact shape representations. However, existing methods encode all shapes into a fixed-size token, disre…