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Interior design is a requirements-to-visual-plan generation process that must simultaneously satisfy verifiable spatial feasibility and comparative aesthetic preferences. While recent multimodal large language models (MLLMs) offer a unified…

Multimedia · Computer Science 2026-03-17 Yuxuan Yang , Xiaotong Mao , Jingyao Wang , Fuchun Sun

As multimodal large language models (MLLMs) are increasingly integrated into early-stage design tools, it is important to understand how designers collaborate with AI during ideation. In a user study with 12 participants, we analysed…

Human-Computer Interaction · Computer Science 2026-03-03 Weiyan Shi , Kenny Tsu Wei Choo

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current models still face misalignment issues (e.g., problematic spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Leigang Qu , Shengqiong Wu , Hao Fei , Liqiang Nie , Tat-Seng Chua

3D scene understanding has gained significant attention due to its wide range of applications. However, existing methods for 3D scene understanding are limited to specific downstream tasks, which hinders their practicality in real-world…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Zehan Wang , Haifeng Huang , Yang Zhao , Ziang Zhang , Zhou Zhao

Spatial intelligence is a critical frontier for Multimodal Large Language Models (MLLMs), empowering them to comprehend the physical world. Drawing inspiration from human perception mechanisms, prior studies attempt to construct a spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yibin Huang , Wang Xu , Wanyue Zhang , Helu Zhi , Jingjing Huang , Yangbin Xu , Yangang Sun , Conghui Zhu , Tiejun Zhao

Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via structured discussion. However, we find that current MAD methods easily suffer from discussion…

Artificial Intelligence · Computer Science 2026-05-14 Xingyuan Hua , Sheng Yue , Xinyi Li , Yizhe Zhao , Jinrui Zhang , Ju Ren

Recent advancements in multi-modal large language models (MLLMs) have shown strong potential for 3D scene understanding. However, existing methods struggle with fine-grained object grounding and contextual reasoning, limiting their ability…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Haifeng Huang , Yilun Chen , Zehan Wang , Jiangmiao Pang , Zhou Zhao

Multi-task policy search is a challenging problem because policies are required to generalize beyond training cases. Curriculum learning has proven to be effective in this setting, as it introduces complexity progressively. However,…

Neural and Evolutionary Computing · Computer Science 2026-02-12 Berfin Sakallioglu , Giorgia Nadizar , Eric Medvet

Sketching in 3D space enables expressive reasoning about shape, structure, and spatial relationships, yet generating 3D sketches through natural language remains a major challenge. In this work, we introduce 3DrawAgent, a training-free,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Hongcan Xiao , Xinyue Xiao , Yilin Wang , Yue Zhang , Yonggang Qi

Large Language Models (LLMs) have demonstrated exceptional proficiency in text understanding and embedding tasks. However, their potential in multimodal representation, particularly for item-to-item (I2I) recommendations, remains…

Information Retrieval · Computer Science 2025-01-22 Chao Zhang , Haoxin Zhang , Shiwei Wu , Di Wu , Tong Xu , Xiangyu Zhao , Yan Gao , Yao Hu , Enhong Chen

Conditional graphic layout generation, which automatically maps user constraints to high-quality layouts, has attracted widespread attention today. Although recent works have achieved promising performance, the lack of versatility and data…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Jiawei Lin , Jiaqi Guo , Shizhao Sun , Zijiang James Yang , Jian-Guang Lou , Dongmei Zhang

Chatbots via large language models (LLMs) generate fluent responses but often struggle with when to speak, especially for brief, timely listener reactions during ongoing dialogue. We present a multimodal strategy for LLMs, which leverages…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Zikai Liao , Yi Ouyang , Yi-Lun Lee , Chen-Ping Yu , Yi-Hsuan Tsai , Zhaozheng Yin

Multimodal Large Language Models (MLLMs) exhibit impressive capabilities across a variety of tasks, especially when equipped with carefully designed visual prompts. However, existing studies primarily focus on logical reasoning and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Dingning Liu , Cheng Wang , Peng Gao , Renrui Zhang , Xinzhu Ma , Yuan Meng , Zhihui Wang

Advancements in Multimodal Large Language Models (MLLMs) have improved human motion understanding. However, these models remain constrained by their "instruct-only" nature, lacking interactivity and adaptability for diverse analytical…

Artificial Intelligence · Computer Science 2025-02-28 Lei Li , Sen Jia , Jianhao Wang , Zhaochong An , Jiaang Li , Jenq-Neng Hwang , Serge Belongie

Recent advancements in large language models (LLMs) have demonstrated extraordinary comprehension capabilities with remarkable breakthroughs on various vision-language tasks. However, the application of LLMs in generating reliable medical…

Artificial Intelligence · Computer Science 2025-02-18 Xueshen Li , Xinlong Hou , Ziyi Huang , Yu Gan

The remarkable potential of multi-modal large language models (MLLMs) in comprehending both vision and language information has been widely acknowledged. However, the scarcity of 3D scenes-language pairs in comparison to their 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Zeju Li , Chao Zhang , Xiaoyan Wang , Ruilong Ren , Yifan Xu , Ruifei Ma , Xiangde Liu

A navigable agent needs to understand both high-level semantic instructions and precise spatial perceptions. Building navigation agents centered on Multimodal Large Language Models (MLLMs) demonstrates a promising solution due to their…

Robotics · Computer Science 2026-02-18 Zerui Li , Hongpei Zheng , Fangguo Zhao , Aidan Chan , Jian Zhou , Sihao Lin , Shijie Li , Qi Wu

We present a work in progress that explores using a Large Language Model (LLM) as a design material for an interactive museum installation. LLMs offer the possibility of creating chatbots that can facilitate dynamic and human-like…

Human-Computer Interaction · Computer Science 2025-03-31 Maria Padilla Engstrøm , Anders Sundnes Løvlie

Despite the remarkable progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, their application to complex 3D scene manipulation remains underexplored. In this paper, we bridge this critical gap by tackling three…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Zhengfei Kuang , Rui Lin , Long Zhao , Gordon Wetzstein , Saining Xie , Sanghyun Woo

Efficient authoring of vast virtual environments hinges on algorithms that are able to automatically generate content while also being controllable. We propose a method to automatically generate furniture layouts for indoor environments.…

Computer Vision and Pattern Recognition · Computer Science 2019-01-28 Paul Henderson , Kartic Subr , Vittorio Ferrari