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Deformable object manipulation remains a key challenge in developing autonomous robotic systems that can be successfully deployed in real-world scenarios. In this work, we explore the challenges of deformable object manipulation through the…

Robotics · Computer Science 2025-03-05 Alison Bartsch , Amir Barati Farimani

Recent large language models (LLMs) show promise in design tasks, yet a fundamental misalignment persists: design thinking requires iterative intent formulation, while LLMs treat inputs as complete specifications. This challenges design…

Human-Computer Interaction · Computer Science 2026-01-27 Anqi Wang , Zhengyi Li , Xin Tong , Pan Hui

Large Language Models (LLMs) have made significant progress in utilizing tools, but their ability is limited by API availability and the instability of implicit reasoning, particularly when both planning and execution are involved. To…

Computation and Language · Computer Science 2024-06-24 Cheng Qian , Chi Han , Yi R. Fung , Yujia Qin , Zhiyuan Liu , Heng Ji

Recent large language models (LLMs) have demonstrated promising capabilities in modeling real-world knowledge and enhancing knowledge-based generation tasks. In this paper, we further explore the potential of using LLMs to aid in the design…

Robotics · Computer Science 2024-11-04 Weicheng Ma , Luyang Zhao , Chun-Yi She , Yitao Jiang , Alan Sun , Bo Zhu , Devin Balkcom , Soroush Vosoughi

Large language models (LLMs) can provide rich physical descriptions of most worldly objects, allowing robots to achieve more informed and capable grasping. We leverage LLMs' common sense physical reasoning and code-writing abilities to…

Robotics · Computer Science 2024-09-10 William Xie , Maria Valentini , Jensen Lavering , Nikolaus Correll

Architects adopt visual scripting and parametric design tools to explore more expansive design spaces (Coates, 2010), refine their thinking about the geometric logic of their design (Woodbury, 2010), and overcome conventional software…

Computation and Language · Computer Science 2024-12-05 Moritz Rietschel , Fang Guo , Kyle Steinfeld

Large Language Models (LLMs) have been shown to act like planners that can decompose high-level instructions into a sequence of executable instructions. However, current LLM-based planners are only able to operate with a fixed set of…

Robotics · Computer Science 2023-10-25 Meenal Parakh , Alisha Fong , Anthony Simeonov , Tao Chen , Abhishek Gupta , Pulkit Agrawal

Multi-object rearrangement is a crucial skill for service robots, and commonsense reasoning is frequently needed in this process. However, achieving commonsense arrangements requires knowledge about objects, which is hard to transfer to…

Robotics · Computer Science 2023-10-09 Yan Ding , Xiaohan Zhang , Chris Paxton , Shiqi Zhang

3D generation from natural language offers significant potential to reduce expert manual modeling efforts and enhance accessibility to 3D assets. However, existing methods often yield unstructured meshes and exhibit poor interactivity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Shuyuan Zhang , Chenhan Jiang , Zuoou Li , Jiankang Deng

In recent years, efforts have been made to use text information for better user profiling and item characterization in recommendations. However, text information can sometimes be of low quality, hindering its effectiveness for real-world…

Artificial Intelligence · Computer Science 2024-02-15 Yingpeng Du , Ziyan Wang , Zhu Sun , Haoyan Chua , Hongzhi Liu , Zhonghai Wu , Yining Ma , Jie Zhang , Youchen Sun

Robot end users increasingly require accessible means of specifying tasks for robots to perform. Two common end-user programming paradigms include drag-and-drop interfaces and natural language programming. Although natural language…

Artificial Intelligence · Computer Science 2026-05-18 David Porfirio , Vincent Hsiao , Morgan Fine-Morris , Leslie Smith , Laura M. Hiatt

Generative AI models provide a wide range of tools capable of performing complex tasks in a fraction of the time it would take a human. Among these, Large Language Models (LLMs) stand out for their ability to generate diverse texts, from…

Computation and Language · Computer Science 2024-10-07 Baldomero R. Árbol , Dan Casas

Generating executable code from natural language instructions using Large Language Models (LLMs) poses challenges such as semantic ambiguity and understanding taskspecific contexts. To address these issues, we propose a system called…

Software Engineering · Computer Science 2025-03-25 Nirmal Joshua Kapu , Mihit Sreejith

Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the…

Robotics · Computer Science 2024-01-09 Callie Y. Kim , Christine P. Lee , Bilge Mutlu

Object manipulation for rearrangement into a specific goal state is a significant task for collaborative robots. Accurately determining object placement is a key challenge, as misalignment can increase task complexity and the risk of…

Robotics · Computer Science 2025-03-06 Guanqun Cao , Ryan Mckenna , Erich Graf , John Oyekan

Large language models (LLMs) are often augmented with tools to solve complex tasks. By generating code snippets and executing them through task-specific Application Programming Interfaces (APIs), they can offload certain functions to…

Computation and Language · Computer Science 2024-03-14 Lifan Yuan , Yangyi Chen , Xingyao Wang , Yi R. Fung , Hao Peng , Heng Ji

There is a significant potential for coding skills to transition fully to natural language in the future. In this context, large language models (LLMs) have shown impressive natural language processing abilities to generate sophisticated…

Materials Science · Physics 2024-06-25 Prathamesh Satpute , Saurabh Tiwari , Maneet Gupta , Supriyo Ghosh

Recently, Large Language Models (LLMs) have achieved significant success, prompting increased interest in expanding their generative capabilities beyond general text into domain-specific areas. This study investigates the generation of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Jiahao Li , Weijian Ma , Xueyang Li , Yunzhong Lou , Guichun Zhou , Xiangdong Zhou

The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intelligence. Understanding and assessing this intelligence is a…

Robotics · Computer Science 2025-12-03 Fanlong Zeng , Wensheng Gan , Zezheng Huai , Lichao Sun , Hechang Chen , Yongheng Wang , Ning Liu , Philip S. Yu

Clay sculpting is a nuanced, artistic task involving dexterous manipulation with long-horizon planning to achieve high-level goals. As a robotics problem, we formulate clay sculpting as a shape-to-shape matching challenge. Prior deformable…

Robotics · Computer Science 2026-05-19 Peter Schaldenbrand , Jean Oh
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