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The increasing prevalence of Large Language Models (LMs) in critical applications highlights the need for controlled language generation strategies that are not only computationally efficient but that also enjoy performance guarantees. To…

Computation and Language · Computer Science 2026-03-16 Emily Cheng , Carmen Amo Alonso

The rise of generative large language models (LLMs) has opened new opportunities for automating knowledge representation through concept maps, a long-standing pedagogical tool valued for fostering meaningful learning and higher-order…

Computers and Society · Computer Science 2025-09-19 Xiaoming Zhai

Large language models (LLMs) have shown exceptional proficiency in natural language processing but often fall short of generating creative and original responses to open-ended questions. To enhance LLM creativity, our key insight is to…

Computation and Language · Computer Science 2024-08-09 Li-Chun Lu , Shou-Jen Chen , Tsung-Min Pai , Chan-Hung Yu , Hung-yi Lee , Shao-Hua Sun

With the rapid evolution of global autonomous driving technology, the demand for its core sensing hardware, Light Detection and Ranging (LiDAR), is escalating. As the light source part of the LiDAR system, lasers, particularly the…

Large Language Models (LLMs) have revolutionized AI systems by enabling communication with machines using natural language. Recent developments in Generative AI (GenAI) like Vision-Language Models (GPT-4V) and Gemini have shown great…

Computation and Language · Computer Science 2024-07-17 Jakub M. Tomczak

Interacting with Large Language Models (LLMs) for text editing on mobile devices currently requires users to break out of their writing environment and switch to a conversational AI interface. In this paper, we propose to control the LLM…

Human-Computer Interaction · Computer Science 2025-02-12 Tim Zindulka , Jannek Sekowski , Florian Lehmann , Daniel Buschek

With the success of 2D diffusion models, 2D AIGC content has already transformed our lives. Recently, this success has been extended to 3D AIGC, with state-of-the-art methods generating textured 3D models from single images or text.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Junhao Chen , Xiang Li , Xiaojun Ye , Chao Li , Zhaoxin Fan , Hao Zhao

Generative AI is increasingly important in software engineering, including safety engineering, where its use ensures that software does not cause harm to people. This also leads to high quality requirements for generative AI. Therefore, the…

Software Engineering · Computer Science 2024-04-25 Florian Geissler , Karsten Roscher , Mario Trapp

We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets with plausible object interactions or require tedious…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Junwei Zhou , Xueting Li , Lu Qi , Ming-Hsuan Yang

The rapid advancement of Multimodal Large Language Models (MLLMs) has significantly impacted various multimodal tasks. However, these models face challenges in tasks that require spatial understanding within 3D environments. Efforts to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Duo Zheng , Shijia Huang , Liwei Wang

Unlocking spatial reasoning in Multimodal Large Language Models (MLLMs) is crucial for enabling intelligent interaction with 3D environments. While prior efforts often rely on explicit 3D inputs or specialized model architectures, we ask:…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Fangrui Zhu , Hanhui Wang , Yiming Xie , Jing Gu , Tianye Ding , Jianwei Yang , Huaizu Jiang

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Despite recent advances in multimodal content generation enabled by vision-language models (VLMs), their ability to reason about and generate structured 3D scenes remains largely underexplored. This limitation constrains their utility in…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Xinhang Liu , Yu-Wing Tai , Chi-Keung Tang

Controllable generation is a fundamental task in NLP with many applications, providing a basis for function calling to agentic communication. However, even state-of-the-art autoregressive Large Language Models (LLMs) today exhibit…

Computation and Language · Computer Science 2025-09-29 Zhen Xiong , Yujun Cai , Zhecheng Li , Yiwei Wang

This paper introduces a novel method for open-vocabulary 3D scene querying in autonomous driving by combining Language Embedded 3D Gaussians with Large Language Models (LLMs). We propose utilizing LLMs to generate both contextually…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Amirhosein Chahe , Lifeng Zhou

This paper assesses the potential for large language models (LLMs) to serve as assistive tools in the creative writing process, by means of a single, in-depth case study. In the course of the study, we develop interactive and multi-voice…

Computation and Language · Computer Science 2023-12-08 Murray Shanahan , Catherine Clarke

In this paper, we propose RoomPlanner, the first fully automatic 3D room generation framework for painlessly creating realistic indoor scenes with only short text as input. Without any manual layout design or panoramic image guidance, our…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Wenzhuo Sun , Mingjian Liang , Wenxuan Song , Xuelian Cheng , Zongyuan Ge

While Large Language Models (LLMs) have demonstrated impressive reasoning and planning abilities in textual domains and can effectively follow instructions for complex tasks, their ability to understand and manipulate spatial relationships…

Artificial Intelligence · Computer Science 2026-01-27 Sha Li , Stefano Petrangeli , Yu Shen , Xiang Chen , Naren Ramakrishnan

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

Large language models (LLMs), such as GPT series and Llama series have demonstrated strong capabilities in natural language processing, contextual understanding, and text generation. In recent years, researchers are trying to enhance the…

Computation and Language · Computer Science 2024-10-08 Ziyang Chen , Stylios Moscholios
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