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We present a framework for generating physically realizable assembly instructions from natural language descriptions. Unlike unconstrained text-to-3D approaches, our method operates within a discrete parts vocabulary, enforcing geometric…

Artificial Intelligence · Computer Science 2025-12-19 David Noever

The integration of large language models (LLMs) into robotic systems has accelerated progress in embodied artificial intelligence, yet current approaches remain constrained by existing robotic architectures, particularly serial mechanisms.…

Robotics · Computer Science 2025-10-07 Guanglu Jia , Ceng Zhang , Gregory S. Chirikjian

Bionic design refers to an approach of generative creativity in which a target object (e.g. a floor lamp) is designed to contain features of biological source objects (e.g. flowers), resulting in creative biologically-inspired design. In…

Computer Vision and Pattern Recognition · Computer Science 2018-05-22 Simiao Yu , Hao Dong , Pan Wang , Chao Wu , Yike Guo

Generative AI (GenAI) tools are radically expanding the scope and capability of automation in knowledge work such as academic research. While promising for augmenting cognition and streamlining processes, AI-assisted research tools may also…

Human-Computer Interaction · Computer Science 2025-04-22 Runlong Ye , Matthew Varona , Oliver Huang , Patrick Yung Kang Lee , Michael Liut , Carolina Nobre

Large language models (LLMs) show strong potential to support creative tasks, but the role of the interface design is poorly understood. In particular, the effect of different modes of collaboration between humans and LLMs on co-creation…

Human-Computer Interaction · Computer Science 2026-03-10 Sebastian Maier , Manuel Schneider , Stefan Feuerriegel

In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained…

Human-Computer Interaction · Computer Science 2024-03-22 Younes Lakhnati , Max Pascher , Jens Gerken

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

Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with generative AI. However, such models often fail to connect the generated outputs and desired target…

Machine Learning · Computer Science 2026-04-15 Melvin Wong , Yew-Soon Ong , Abhishek Gupta , Kavitesh K. Bali , Caishun Chen

The wide applicability and adaptability of generative large language models (LLMs) has enabled their rapid adoption. While the pre-trained models can perform many tasks, such models are often fine-tuned to improve their performance on…

Computation and Language · Computer Science 2023-06-16 Myles Foley , Ambrish Rawat , Taesung Lee , Yufang Hou , Gabriele Picco , Giulio Zizzo

This Monte Carlo simulation examines how prompt engineering strategies shape the quality of large language model (LLM)--generated personality assessment items within the AI-GENIE framework for generative psychometrics. Item pools targeting…

Artificial Intelligence · Computer Science 2026-03-18 Lara Lee Russell-Lasalandra , Hudson Golino

Generative AI (GenAI) models excel in their ability to recognize patterns in existing data and generate new and unexpected content. Recent advances have motivated applications of GenAI tools (e.g., Stable Diffusion, ChatGPT) to professional…

Human-Computer Interaction · Computer Science 2023-06-05 Matthew K. Hong , Shabnam Hakimi , Yan-Ying Chen , Heishiro Toyoda , Charlene Wu , Matt Klenk

Industrial computer vision systems often struggle with noise, material variability, and uncontrolled imaging conditions, limiting the effectiveness of classical edge detectors and handcrafted pipelines. In this work, we present a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Liang Gong , Tommy , Wang , Sara Chaker , Yanchen Dong , Fouad Bousetouane , Brenden Morton , Mark Mendez

Large Language Models (LLMs) pose a new paradigm of modeling and computation for information tasks. Recommendation systems are a critical application domain poised to benefit significantly from the sequence modeling capabilities and world…

Large Language Models (LLMs) and, more specifically, the Generative Pre-Trained Transformers (GPT) can help stakeholders in climate action explore digital knowledge bases and extract and utilize climate action knowledge in a sustainable…

Computers and Society · Computer Science 2024-02-02 Denis Havlik , Marcelo Pias

This study explores automatic generation (AIG) using language models to create multiple choice questions (MCQs) for morphological assessment, aiming to reduce the cost and inconsistency of manual test development. The study used a two-fold…

Computation and Language · Computer Science 2025-08-29 Mohammad Amini , Babak Ahmadi , Xiaomeng Xiong , Yilin Zhang , Christopher Qiao

Recent advancements in Generative AI, particularly in Large Language Models (LLMs) and Large Vision-Language Models (LVLMs), offer new possibilities for integrating cognitive planning into robotic systems. In this work, we present a novel…

Robotics · Computer Science 2024-11-06 Arjun P S , Andrew Melnik , Gora Chand Nandi

This paper presents LLM2TEA, a Large Language Model (LLM) driven MultiTask Evolutionary Algorithm, representing the first agentic AI designer of its kind operating with generative evolutionary multitasking (GEM). LLM2TEA enables the…

Artificial Intelligence · Computer Science 2025-10-14 Melvin Wong , Jiao Liu , Thiago Rios , Stefan Menzel , Yew Soon Ong

Large language models (LLMs) are increasingly seen as assistants, copilots, and consultants, capable of supporting a wide range of tasks through natural conversation. However, most systems remain constrained by a linear request-response…

Computation and Language · Computer Science 2026-05-05 Jiaqi Chen , Yanzhe Zhang , Yutong Zhang , Yijia Shao , Diyi Yang

Generative artificial intelligence (GenAI) can rapidly produce large and diverse volumes of content. This lends to it a quality of creativity which can be empowering in the early stages of design. In seeking to understand how creative ways…

Human-Computer Interaction · Computer Science 2024-03-20 Gionnieve Lim , Simon T. Perrault

We propose a new concept, Evolution 6.0, which represents the evolution of robotics driven by Generative AI. When a robot lacks the necessary tools to accomplish a task requested by a human, it autonomously designs the required instruments…