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Related papers: Large Language and Text-to-3D Models for Engineeri…

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Large language models (LLMs) have not only revolutionized natural language processing but also extended their prowess to various domains, marking a significant stride towards artificial general intelligence. The interplay between LLMs and…

Neural and Evolutionary Computing · Computer Science 2024-05-30 Xingyu Wu , Sheng-hao Wu , Jibin Wu , Liang Feng , Kay Chen Tan

Text-to-3D generation automates 3D content creation from textual descriptions, which offers transformative potential across various fields. However, existing methods often struggle to align generated content with human preferences, limiting…

Computation and Language · Computer Science 2025-02-10 Zhenglin Zhou , Xiaobo Xia , Fan Ma , Hehe Fan , Yi Yang , Tat-Seng Chua

Computer-aided design (CAD) is fundamental to modern engineering and manufacturing, but creating CAD models still requires expert knowledge and specialized software. Recent advances in large language models (LLMs) open up the possibility of…

Artificial Intelligence · Computer Science 2025-05-13 Haoyang Xie , Feng Ju

Open AI's language model, GPT-3, has shown great potential for many NLP tasks, with applications in many different domains. In this work we carry out a first study on GPT-3's capability to communicate musical decisions through textual…

Computation and Language · Computer Science 2022-06-17 Stephen James Krol , Maria Teresa Llano , Jon McCormack

This survey reviews how large language models (LLMs) are transforming synthetic training data generation in both natural language and code domains. By producing artificial but task-relevant examples, these models can significantly augment…

Computation and Language · Computer Science 2025-11-21 Mihai Nadas , Laura Diosan , Andreea Tomescu

The evolution of wireless networks gravitates towards connected intelligence, a concept that envisions seamless interconnectivity among humans, objects, and intelligence in a hyper-connected cyber-physical world. Edge artificial…

Information Theory · Computer Science 2023-12-27 Yifei Shen , Jiawei Shao , Xinjie Zhang , Zehong Lin , Hao Pan , Dongsheng Li , Jun Zhang , Khaled B. Letaief

In this paper, we conduct a comprehensive SWOT analysis of prompt engineering techniques within the realm of Large Language Models (LLMs). Emphasizing linguistic principles, we examine various techniques to identify their strengths,…

Computation and Language · Computer Science 2024-10-18 Aditi Singh , Abul Ehtesham , Gaurav Kumar Gupta , Nikhil Kumar Chatta , Saket Kumar , Tala Talaei Khoei

Prompt engineering, as an efficient and effective way to leverage Large Language Models (LLM), has drawn a lot of attention from the research community. The existing research primarily emphasizes the importance of adapting prompts to…

Computation and Language · Computer Science 2024-07-08 Yuyan Chen , Zhihao Wen , Ge Fan , Zhengyu Chen , Wei Wu , Dayiheng Liu , Zhixu Li , Bang Liu , Yanghua Xiao

We introduce the concept of "Design Agents" for engineering applications, particularly focusing on the automotive design process, while emphasizing that our approach can be readily extended to other engineering and design domains. Our…

Artificial Intelligence · Computer Science 2025-12-04 Mohamed Elrefaie , Janet Qian , Raina Wu , Qian Chen , Angela Dai , Faez Ahmed

Traditional optimization methods excel in well-defined search spaces but struggle with design problems where transformations and design parameters are difficult to define. Large language models (LLMs) offer a promising alternative by…

Machine Learning · Computer Science 2025-12-01 Anthony Carreon , Vansh Sharma , Venkat Raman

Computer Aided Design (CAD) is indispensable across various industries. \emph{Text-based CAD editing}, which automates the modification of CAD models based on textual instructions, holds great potential but remains underexplored. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Yu Yuan , Shizhao Sun , Qi Liu , Jiang Bian

Most large language models (LLMs) are sensitive to prompts, and another synonymous expression or a typo may lead to unexpected results for the model. Composing an optimal prompt for a specific demand lacks theoretical support and relies…

Computation and Language · Computer Science 2024-06-18 Zhenyu Zhang , Bingguang Hao , Jinpeng Li , Zekai Zhang , Dongyan Zhao

Boosted by deep learning, natural language processing (NLP) techniques have recently seen spectacular progress, mainly fueled by breakthroughs both in representation learning with word embeddings (e.g. word2vec) as well as novel…

Networking and Internet Architecture · Computer Science 2022-07-26 Zied Ben Houidi , Dario Rossi

Large Language Models (LLMs) have demonstrated remarkable in-context learning capabilities, enabling flexible utilization of limited historical information to play pivotal roles in reasoning, problem-solving, and complex pattern recognition…

Machine Learning · Computer Science 2025-03-31 Zhonglin Jiang , Qian Tang , Zequn Wang

Despite impressive recent advances in text-to-image diffusion models, obtaining high-quality images often requires prompt engineering by humans who have developed expertise in using them. In this work, we present NeuroPrompts, an adaptive…

Artificial Intelligence · Computer Science 2024-04-09 Shachar Rosenman , Vasudev Lal , Phillip Howard

In recent years, the use of deep learning in language models gained much attention. Some research projects claim that they can generate text that can be interpreted as human-writing, enabling new possibilities in many application areas.…

Computation and Language · Computer Science 2021-01-13 Juan Cruz-Benito , Sanjay Vishwakarma , Francisco Martin-Fernandez , Ismael Faro

Computer-aided design (CAD) is vital to modern manufacturing, yet model creation remains labor-intensive and expertise-heavy. To enable non-experts to translate intuitive design intent into manufacturable artifacts, recent large language…

Artificial Intelligence · Computer Science 2026-01-21 Xiangyu Shi , Junyang Ding , Xu Zhao , Sinong Zhan , Payal Mohapatra , Daniel Quispe , Kojo Welbeck , Jian Cao , Wei Chen , Ping Guo , Qi Zhu

We present Shap-MeD, a text-to-3D object generative model specialized in the biomedical domain. The objective of this study is to develop an assistant that facilitates the 3D modeling of medical objects, thereby reducing development time.…

Graphics · Computer Science 2025-03-21 Nicolás Laverde , Melissa Robles , Johan Rodríguez

Automated heuristic design (AHD) has gained considerable attention for its potential to automate the development of effective heuristics. The recent advent of large language models (LLMs) has paved a new avenue for AHD, with initial efforts…

Neural and Evolutionary Computing · Computer Science 2024-07-16 Rui Zhang , Fei Liu , Xi Lin , Zhenkun Wang , Zhichao Lu , Qingfu Zhang

The ability of Large Language Models (LLMs) to generate high-quality text and code has fuelled their rise in popularity. In this paper, we aim to demonstrate the potential of LLMs within the realm of optimization algorithms by integrating…

Artificial Intelligence · Computer Science 2024-02-14 Camilo Chacón Sartori , Christian Blum , Gabriela Ochoa