1-19 of 19
Large language models
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Human-Artificial Intelligence Teaming for Scientific Information Extraction From Data-Driven Additive Manufacturing Research Using Large Language Models

Mutahar Safdar, Jiarui Xie, Andrei Mircea, Yaoyao Fiona Zhao
Proc. ASME. IDETC-CIE2024, Volume 2A: 44th Computers and Information in Engineering Conference (CIE), V02AT02A028, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-142857
https://doi.org/10.1115/DETC2024-142857
View Paper titled, Human-Artificial Intelligence Teaming for Scientific Information Extraction From Data-Driven Additive Manufacturing Research Using Large Language Models
Open the PDF for Human-Artificial Intelligence Teaming for Scientific Information Extraction From Data-Driven Additive Manufacturing Research Using Large Language Models in another window
Topics: Additive manufacturing, Design, Large language models, Manufacturing
Proceedings Papers

Can an LLM Learn an Unseen Engineering Language? An Empirical Study of Prompt Engineering on ChatGPT and Function Modeling

Armando Loynaz, Cassandra Stanish, Aria Treeman-Reinke, Sebastian Donall, Chiradeep Sen
Proc. ASME. IDETC-CIE2024, Volume 2B: 44th Computers and Information in Engineering Conference (CIE), V02BT02A045, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143824
https://doi.org/10.1115/DETC2024-143824
View Paper titled, Can an LLM Learn an Unseen Engineering Language? An Empirical Study of Prompt Engineering on ChatGPT and Function Modeling
Open the PDF for Can an LLM Learn an Unseen Engineering Language? An Empirical Study of Prompt Engineering on ChatGPT and Function Modeling in another window
Topics: Chatgpt, Large language models, Modeling
Proceedings Papers

Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models

Lukman Irshad, Hannah Walsh
Proc. ASME. IDETC-CIE2024, Volume 2B: 44th Computers and Information in Engineering Conference (CIE), V02BT02A017, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143591
https://doi.org/10.1115/DETC2024-143591
View Paper titled, Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models
Open the PDF for Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models in another window
Topics: Accidents, Errors, Large language models
Proceedings Papers

Leveraging Latent Textual Topology for Standard Identification in Engineering Design

Matthew Bowen, Logan Smith, Cody Carroll, Beshoy Morkos
Proc. ASME. IDETC-CIE2024, Volume 2B: 44th Computers and Information in Engineering Conference (CIE), V02BT02A012, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-146285
https://doi.org/10.1115/DETC2024-146285
View Paper titled, Leveraging Latent Textual Topology for Standard Identification in Engineering Design
Open the PDF for Leveraging Latent Textual Topology for Standard Identification in Engineering Design in another window
Topics: Engineering design, Large language models, Topology
Proceedings Papers

DesignQA: Benchmarking Multimodal Large Language Models on Questions Grounded in Engineering Documentation

Anna C. Doris, Daniele Grandi, Ryan Tomich, Md Ferdous Alam, Hyunmin Cheong, Faez Ahmed
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A016, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-139024
https://doi.org/10.1115/DETC2024-139024
View Paper titled, DesignQA: Benchmarking Multimodal Large Language Models on Questions Grounded in Engineering Documentation
Open the PDF for DesignQA: Benchmarking Multimodal Large Language Models on Questions Grounded in Engineering Documentation in another window
Topics: Large language models, Design, Computer-aided design, Engineering design processes, Engineering drawings, Engineers, Student competitions
Proceedings Papers

Generating Porous Metamaterial Designs Using Variational Graph Autoencoder and Large Language Model

Kiarash Naghavi Khanghah, Zihan Wang, Hongyi Xu
Proc. ASME. IDETC-CIE2024, Volume 3A: 50th Design Automation Conference (DAC), V03AT03A007, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143234
https://doi.org/10.1115/DETC2024-143234
View Paper titled, Generating Porous Metamaterial Designs Using Variational Graph Autoencoder and Large Language Model
Open the PDF for Generating Porous Metamaterial Designs Using Variational Graph Autoencoder and Large Language Model in another window
Topics: Large language models, Metamaterials
Proceedings Papers

Designing Fictional Worlds for Play Through Large Language Models

Ada-Rhodes Short
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A051, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143923
https://doi.org/10.1115/DETC2024-143923
View Paper titled, Designing Fictional Worlds for Play Through Large Language Models
Open the PDF for Designing Fictional Worlds for Play Through Large Language Models in another window
Topics: Design, Large language models, Woodworking, Artificial intelligence, Chatgpt, Creativity, Generative artificial intelligence
Proceedings Papers

ConceptVis: Generating and Exploring Design Concepts for Early-Stage Ideation Using Large Language Model

Runlin Duan, Nachiketh Karthik, Jingyu Shi, Rahul Jain, Maria C. Yang, Karthik Ramani
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A042, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-146409
https://doi.org/10.1115/DETC2024-146409
View Paper titled, ConceptVis: Generating and Exploring Design Concepts for Early-Stage Ideation Using Large Language Model
Open the PDF for ConceptVis: Generating and Exploring Design Concepts for Early-Stage Ideation Using Large Language Model in another window
Topics: Design, Large language models, Visualization
Proceedings Papers

Extending the Product Architecture Strategies and Effects Database Through Large Language Models

Scott E. Rice, Benjamin C. Sannar, Christopher A. Mattson, Michael A. Anderson
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A057, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143663
https://doi.org/10.1115/DETC2024-143663
View Paper titled, Extending the Product Architecture Strategies and Effects Database Through Large Language Models
Open the PDF for Extending the Product Architecture Strategies and Effects Database Through Large Language Models in another window
Topics: Databases, Large language models, Product architecture
Proceedings Papers

Elicitron: A Framework for Simulating Design Requirements Elicitation Using Large Language Model Agents

Mohammadmehdi Ataei, Hyunmin Cheong, Daniele Grandi, Ye Wang, Nigel Morris, Alexander Tessier
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A056, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143598
https://doi.org/10.1115/DETC2024-143598
View Paper titled, Elicitron: A Framework for Simulating Design Requirements Elicitation Using Large Language Model Agents
Open the PDF for Elicitron: A Framework for Simulating Design Requirements Elicitation Using Large Language Model Agents in another window
Topics: Design, Large language models, Product development, Chain, Innovation, Machine learning, Simulation
Proceedings Papers

AutoTRIZ: Artificial Ideation With TRIZ and Large Language Models

Shuo Jiang, Jianxi Luo
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A055, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143166
https://doi.org/10.1115/DETC2024-143166
View Paper titled, AutoTRIZ: Artificial Ideation With TRIZ and Large Language Models
Open the PDF for AutoTRIZ: Artificial Ideation With TRIZ and Large Language Models in another window
Topics: Artificial intelligence, Design, Innovation, Large language models
Proceedings Papers

A Case Study of Design Concept Generation Based on Knowledge Operation With a Large Language Model: Architectural Design Using Christopher Alexander’s Pattern Language

Daichi Tanaka, Kei Kuroishi, Akira Utsunomiya, Yutaka Nomaguchi, Kikuo Fujita
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A059, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143848
https://doi.org/10.1115/DETC2024-143848
View Paper titled, A Case Study of Design Concept Generation Based on Knowledge Operation With a Large Language Model: Architectural Design Using Christopher Alexander’s Pattern Language
Open the PDF for A Case Study of Design Concept Generation Based on Knowledge Operation With a Large Language Model: Architectural Design Using Christopher Alexander’s Pattern Language in another window
Topics: Design, Large language models
Proceedings Papers

Material Selection Using Large Language Models

Yash Patawari Jain, Daniele Grandi, Allin Groom, Brandon Cramer, Christopher McComb
Proc. ASME. IDETC-CIE2024, Volume 3B: 50th Design Automation Conference (DAC), V03BT03A058, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143751
https://doi.org/10.1115/DETC2024-143751
View Paper titled, Material Selection Using Large Language Models
Open the PDF for Material Selection Using Large Language Models in another window
Topics: Large language models, Design, Conceptual design, Manufacturing, Architecture, Construction, Cycles, Natural language processing, Optimization, Preferences
Proceedings Papers

TRIZ-GPT: An LLM-Augmented Method For Problem-Solving

Liuqing Chen, Yaxuan Song, Shixian Ding, Lingyun Sun, Peter Childs, Haoyu Zuo
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A010, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143163
https://doi.org/10.1115/DETC2024-143163
View Paper titled, TRIZ-GPT: An LLM-Augmented Method For Problem-Solving
Open the PDF for TRIZ-GPT: An LLM-Augmented Method For Problem-Solving in another window
Topics: Large language models
Proceedings Papers

A Picture or a Thousand Words: Design Description Crafting to Replicate Human Similarity Judgments in Large Language Models

Matthew Keeler, Mark Fuge, Aoran Peng, Scarlett Miller
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A012, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143634
https://doi.org/10.1115/DETC2024-143634
View Paper titled, A Picture or a Thousand Words: Design Description Crafting to Replicate Human Similarity Judgments in Large Language Models
Open the PDF for A Picture or a Thousand Words: Design Description Crafting to Replicate Human Similarity Judgments in Large Language Models in another window
Topics: Design, Large language models, Crowdsourcing, Engineering design, Modeling
Proceedings Papers

LLM4CAD: Multi-Modal Large Language Models for 3D Computer-Aided Design Generation

Xingang Li, Yuewan Sun, Zhenghui Sha
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A015, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143740
https://doi.org/10.1115/DETC2024-143740
View Paper titled, LLM4CAD: Multi-Modal Large Language Models for 3D Computer-Aided Design Generation
Open the PDF for LLM4CAD: Multi-Modal Large Language Models for 3D Computer-Aided Design Generation in another window
Topics: Computer-aided design, Large language models, Three-dimensional computer-aided design
Proceedings Papers

Emulating Cognitive Style in Large Language Models

Vasvi Agarwal, Kathryn Jablokow, Christopher McComb
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A002, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143677
https://doi.org/10.1115/DETC2024-143677
View Paper titled, Emulating Cognitive Style in Large Language Models
Open the PDF for Emulating Cognitive Style in Large Language Models in another window
Topics: Large language models, Design, Innovation, Teams
Proceedings Papers

Augmenting Engineering Design With AI: Introducing the AI Design Assistant (AIDA)

Naveen Mathews Renji, Sagar Chakravarthy Mathada Veera, Bei Yan, Ting Liao
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A016, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143765
https://doi.org/10.1115/DETC2024-143765
View Paper titled, Augmenting Engineering Design With AI: Introducing the AI Design Assistant (AIDA)
Open the PDF for Augmenting Engineering Design With AI: Introducing the AI Design Assistant (AIDA) in another window
Topics: Design, Engineering design, Large language models
Proceedings Papers

Reading Users’ Minds from What They Say: An Investigation into LLM-based Empathic Mental Inference

Qihao Zhu, Leah Chong, Maria Yang, Jianxi Luo
Proc. ASME. IDETC-CIE2024, Volume 6: 36th International Conference on Design Theory and Methodology (DTM), V006T06A018, August 25–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: DETC2024-143961
https://doi.org/10.1115/DETC2024-143961
View Paper titled, Reading Users’ Minds from What They Say: An Investigation into LLM-based Empathic Mental Inference
Open the PDF for Reading Users’ Minds from What They Say: An Investigation into LLM-based Empathic Mental Inference in another window
Topics: Artificial intelligence, Design, Large language models, Product design