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Recent research has been increasingly focusing on developing 3D world models that simulate complex real-world scenarios. World models have found broad applications across various domains, including embodied AI, autonomous driving,…

Artificial Intelligence · Computer Science 2025-09-09 Yinglin Duan , Zhengxia Zou , Tongwei Gu , Wei Jia , Zhan Zhao , Luyi Xu , Xinzhu Liu , Yenan Lin , Hao Jiang , Kang Chen , Shuang Qiu

Requirements elicitation, a critical, yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This may lead to products that fall short of expectations. This paper introduces a…

Human-Computer Interaction · Computer Science 2024-04-26 Mohammadmehdi Ataei , Hyunmin Cheong , Daniele Grandi , Ye Wang , Nigel Morris , Alexander Tessier

We propose LLM-Interleaved (LLM-I), a flexible and dynamic framework that reframes interleaved image-text generation as a tool-use problem. LLM-I is designed to overcome the "one-tool" bottleneck of current unified models, which are limited…

Machine Learning · Computer Science 2025-09-18 Zirun Guo , Feng Zhang , Kai Jia , Tao Jin

Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further unleash the power of LLMs to accomplish complex tasks, there…

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

Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Recent large vision-language models (LVLMs) for video understanding are primarily fine-tuned with various videos scraped from online platforms. Existing datasets, such as ActivityNet, require considerable human labor for structuring and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhende Song , Chenchen Wang , Jiamu Sheng , Chi Zhang , Shengji Tang , Jiayuan Fan , Tao Chen

Large Language Models (LLMs) have demonstrated remarkable proficiency in generating highly structured texts. However, while exhibiting a high degree of structural organization, movie scripts demand an additional layer of nuanced…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mingzhe Zheng , Dingjie Song , Guanyu Zhou , Jun You , Jiahao Zhan , Xuran Ma , Xinyuan Song , Ser-Nam Lim , Qifeng Chen , Harry Yang

Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and physical complexity of real indoor spaces. Current scene synthesis methods produce sparsely…

Robotics · Computer Science 2026-02-12 Nicholas Pfaff , Thomas Cohn , Sergey Zakharov , Rick Cory , Russ Tedrake

3D generation from natural language offers significant potential to reduce expert manual modeling efforts and enhance accessibility to 3D assets. However, existing methods often yield unstructured meshes and exhibit poor interactivity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Shuyuan Zhang , Chenhan Jiang , Zuoou Li , Jiankang Deng

Large language models (LLMs) are increasingly leveraged to empower autonomous agents to simulate human beings in various fields of behavioral research. However, evaluating their capacity to navigate complex social interactions remains a…

Computation and Language · Computer Science 2024-11-26 Xinyi Mou , Jingcong Liang , Jiayu Lin , Xinnong Zhang , Xiawei Liu , Shiyue Yang , Rong Ye , Lei Chen , Haoyu Kuang , Xuanjing Huang , Zhongyu Wei

This technical report presents the Drama Engine, a novel framework for agentic interaction with large language models designed for narrative purposes. The framework adapts multi-agent system principles to create dynamic, context-aware…

Artificial Intelligence · Computer Science 2024-08-22 Martin Pichlmair , Riddhi Raj , Charlene Putney

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Ian Huang , Guandao Yang , Leonidas Guibas

Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reasoning and tool-use steps, leaving control flow and intermediate state implicit and making…

Computation and Language · Computer Science 2026-04-16 Pengcheng Wang , Jerry Huang , Jiarui Yao , Rui Pan , Peizhi Niu , Yaowenqi Liu , Ruida Wang , Renhao Lu , Yuwei Guo , Tong Zhang

As LLM-based agents are increasingly deployed in real-life scenarios, existing benchmarks fail to capture their inherent complexity of handling extensive information, leveraging diverse resources, and managing dynamic user interactions. To…

Computation and Language · Computer Science 2025-10-20 Wei He , Yueqing Sun , Hongyan Hao , Xueyuan Hao , Zhikang Xia , Qi Gu , Chengcheng Han , Dengchang Zhao , Hui Su , Kefeng Zhang , Man Gao , Xi Su , Xiaodong Cai , Xunliang Cai , Yu Yang , Yunke Zhao

As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether they can generate correct, reusable, and executable skills from repositories and…

Artificial Intelligence · Computer Science 2026-05-19 Yifan Zhou , Zhentao Zhang , Ziming Cheng , Shuo Zhang , Qizhen Lan , Zhangquan Chen , Zhi Yang , QianyuXu , Ronghao Chen , Huacan Wang , Sen Hu

Designing complex computer-aided design (CAD) models is often time-consuming due to challenges such as computational inefficiency and the difficulty of generating precise models. We propose a novel language-guided framework for industrial…

Artificial Intelligence · Computer Science 2025-05-27 Jianxing Liao , Junyan Xu , Yatao Sun , Maowen Tang , Sicheng He , Jingxian Liao , Shui Yu , Yun Li , Hongguan Xiao

Creating effective dialogue systems for mental health support requires high-quality multi-turn counseling dialogue data, yet collecting real counselor-client conversations presents significant challenges, including privacy concerns, high…

Computation and Language · Computer Science 2026-05-27 Huachuan Qiu , Zhenzhong Lan

Recent advancements in large language models (LLMs) have revealed their potential for achieving autonomous agents possessing human-level intelligence. However, existing benchmarks for evaluating LLM Agents either use static datasets,…

Computation and Language · Computer Science 2024-02-27 Junzhe Chen , Xuming Hu , Shuodi Liu , Shiyu Huang , Wei-Wei Tu , Zhaofeng He , Lijie Wen