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Industry 4.0 has revolutionized manufacturing by driving digitalization and shifting the paradigm toward additive manufacturing (AM). Fused Deposition Modeling (FDM), a key AM technology, enables the creation of highly customized,…

Computation and Language · Computer Science 2026-01-01 Yayati Jadhav , Peter Pak , Amir Barati Farimani

Pharmaceutical three-dimensional (3D) printing is an advanced fabrication technology with the potential to enable truly personalised dosage forms. Recent studies have integrated artificial intelligence (AI) to accelerate formulation and…

Artificial Intelligence · Computer Science 2026-05-19 Adeshola Okubena , Yusuf Ali Mohammed , Moe Elbadawi

Additive manufacturing (AM) continues to transform modern manufacturing by enabling flexible, on-demand production of complex geometries across diverse industries. Fused filament fabrication (FFF) has extended AM to laboratories,…

Machine Learning · Computer Science 2026-05-06 Ahmadreza Eslaminia , Chuhan Cai , Cameron Smith , Ruo-Syuan Mei , Shichen Li , Rajiv Malhotra , Klara Nahrstedt , Chenhui Shao

3D printing or additive manufacturing is a revolutionary technology that enables the creation of physical objects from digital models. However, the quality and accuracy of 3D printing depend on the correctness and efficiency of the G-code,…

Software Engineering · Computer Science 2023-09-07 Anushrut Jignasu , Kelly Marshall , Baskar Ganapathysubramanian , Aditya Balu , Chinmay Hegde , Adarsh Krishnamurthy

We use fused deposition modeling (FDM) 3D printing as a case study of how manufacturing robots can use imperfect AI to acquire process expertise. In FDM, print configuration strongly affects output quality. Yet, novice users typically rely…

Robotics · Computer Science 2026-03-24 Ekta U. Samani , Christopher G. Atkeson

Although large language models (LLMs) have demonstrated their strong intelligence ability, the high demand for computation and storage hinders their practical application. To this end, many model compression techniques are proposed to…

Computation and Language · Computer Science 2024-11-01 Ge Yang , Changyi He , Jinyang Guo , Jianyu Wu , Yifu Ding , Aishan Liu , Haotong Qin , Pengliang Ji , Xianglong Liu

Large Language Models (LLMs) have demonstrated strong performance across general NLP tasks, but their utility in automating numerical experiments of complex physical system -- a critical and labor-intensive component -- remains…

Computation and Language · Computer Science 2026-04-28 Nithin Somasekharan , Ling Yue , Yadi Cao , Weichao Li , Patrick Emami , Pochinapeddi Sai Bhargav , Anurag Acharya , Xingyu Xie , Shaowu Pan

Large Language Diffusion Models (LLDMs) benefit from a flexible decoding mechanism that enables parallelized inference and controllable generations over autoregressive models. Yet such flexibility introduces a critical challenge: inference…

Machine Learning · Computer Science 2025-12-05 Yichuan Mo , Quan Chen , Mingjie Li , Zeming Wei , Yisen Wang

Large language models (LLMs) are effective at capturing complex, valuable conceptual representations from textual data for a wide range of real-world applications. However, in fields like Intelligent Fault Diagnosis (IFD), incorporating…

Artificial Intelligence · Computer Science 2024-12-03 Hamzah A. A. M. Qaid , Bo Zhang , Dan Li , See-Kiong Ng , Wei Li

The integration of large language models (LLMs) into automated algorithm design has shown promising potential. A prevalent approach embeds LLMs within search routines to iteratively generate and refine candidate algorithms. However, most…

Machine Learning · Computer Science 2026-05-20 Fei Liu , Rui Zhang , Xi Lin , Zhichao Lu , Qingfu Zhang

Conventional mechanical design follows an iterative process in which initial concepts are refined through cycles of expert assessment and resource-intensive Finite Element Method (FEM) analysis to meet performance goals. While machine…

Machine Learning · Computer Science 2025-05-02 Yayati Jadhav , Amir Barati Farimani

Federated learning has enabled multiple parties to collaboratively train large language models without directly sharing their data (FedLLM). Following this training paradigm, the community has put massive efforts from diverse aspects…

Computation and Language · Computer Science 2024-06-10 Rui Ye , Rui Ge , Xinyu Zhu , Jingyi Chai , Yaxin Du , Yang Liu , Yanfeng Wang , Siheng Chen

Vision-Language Models (VLMs) have demonstrated remarkable capabilities in cross-modal understanding and generation by integrating visual and textual information. While instruction tuning and parameter-efficient fine-tuning methods have…

Machine Learning · Computer Science 2025-06-12 Weiying Zheng , Ziyue Lin , Pengxin Guo , Yuyin Zhou , Feifei Wang , Liangqiong Qu

The advent of large language models (LLMs) revolutionized natural language processing applications, and running LLMs on edge devices has become increasingly attractive for reasons including reduced latency, data localization, and…

Computation and Language · Computer Science 2024-09-17 Jiajun Xu , Zhiyuan Li , Wei Chen , Qun Wang , Xin Gao , Qi Cai , Ziyuan Ling

Large Language Models (LLM) and foundation models are popular as they offer new opportunities for individuals and businesses to improve natural language processing, interact with data, and retrieve information faster. However, training or…

Machine Learning · Computer Science 2024-05-03 Herbert Woisetschläger , Alexander Isenko , Shiqiang Wang , Ruben Mayer , Hans-Arno Jacobsen

Additive manufacturing (AM) has transformed the production landscape by enabling the precision creation of complex geometries. However, AM faces limitations when applied to challenging environments, such as elevated surfaces and remote…

Robotics · Computer Science 2025-03-25 Akshay Raman , Chad Merrill , Abraham George , Amir Barati Farimani

LLMs have demonstrated great capabilities in various NLP tasks. Different entities can further improve the performance of those LLMs on their specific downstream tasks by fine-tuning LLMs. When several entities have similar interested…

Machine Learning · Computer Science 2023-09-04 Weirui Kuang , Bingchen Qian , Zitao Li , Daoyuan Chen , Dawei Gao , Xuchen Pan , Yuexiang Xie , Yaliang Li , Bolin Ding , Jingren Zhou

Large Language Models (LLMs), such as ChatGPT, LLaMA, GLM, and PaLM, have exhibited remarkable performances across various tasks in recent years. However, LLMs face two main challenges in real-world applications. One challenge is that…

Machine Learning · Computer Science 2023-10-17 Tao Fan , Yan Kang , Guoqiang Ma , Weijing Chen , Wenbin Wei , Lixin Fan , Qiang Yang

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has…

Machine Learning · Computer Science 2024-07-26 Mohammad Karimzadeh , Deekshith Basvoju , Aleksandar Vakanski , Indrajit Charit , Fei Xu , Xinchang Zhang

Large Language Models (LLMs) have demonstrated impressive success across various tasks. Integrating LLMs with Federated Learning (FL), a paradigm known as FedLLM, offers a promising avenue for collaborative model adaptation while preserving…

Machine Learning · Computer Science 2026-02-25 Yebo Wu , Chunlin Tian , Jingguang Li , He Sun , Kahou Tam , Zhanting Zhou , Haicheng Liao , Jing Xiong , Zhijiang Guo , Li Li , Chengzhong Xu
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