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Large Language Models (LLMs) drive current AI breakthroughs despite very little being known about their internal representations. In this work, we propose to shed the light on LLMs inner mechanisms through the lens of geometry. In…

人工智能 · 计算机科学 2024-07-12 Randall Balestriero , Romain Cosentino , Sarath Shekkizhar

This thesis presents a framework that integrates state-of-the-art generative AI models for real-time creation of three-dimensional (3D) objects in augmented reality (AR) environments. The primary goal is to convert diverse inputs, such as…

图形学 · 计算机科学 2025-02-25 Majid Behravan

Significant advancements have been made in one of the most critical branches of artificial intelligence: natural language processing (NLP). These advancements are exemplified by the remarkable success of OpenAI's GPT-3.5/4 and the recent…

材料科学 · 物理学 2025-04-22 Zongrui Pei , Junqi Yin , Jiaxin Zhang

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate…

计算机视觉与模式识别 · 计算机科学 2024-05-30 Chunyi Sun , Junlin Han , Weijian Deng , Xinlong Wang , Zishan Qin , Stephen Gould

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…

计算与语言 · 计算机科学 2025-11-21 Mihai Nadas , Laura Diosan , Andreea Tomescu

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…

机器学习 · 计算机科学 2025-05-02 Yayati Jadhav , Amir Barati Farimani

Large Language Models (LLMs) represent a leap in artificial intelligence, excelling in tasks using human language(s). Although the main focus of general-purpose LLMs is not code generation, they have shown promising results in the domain.…

软件工程 · 计算机科学 2024-01-30 Sanka Rasnayaka , Guanlin Wang , Ridwan Shariffdeen , Ganesh Neelakanta Iyer

This paper explores ideas and provides a potential roadmap for the development and evaluation of physics-specific large-scale AI models, which we call Large Physics Models (LPMs). These models, based on foundation models such as Large…

While recent advancements in machine learning, such as LLMs, are revolutionizing software development and creative industries, they have had minimal impact on engineers designing mechanical parts, which remains largely a manual process.…

机器学习 · 计算机科学 2025-05-07 Maximilian Mews , Ansar Aynetdinov , Vivian Schiller , Peter Eisert , Alan Akbik

Existing generative models for 3D shapes can synthesize high-fidelity and visually plausible shapes. For certain classes of shapes that have undergone an engineering design process, the realism of the shape is tightly coupled with the…

计算机视觉与模式识别 · 计算机科学 2026-03-24 Yingxuan You , Chen Zhao , Hantao Zhang , Ming Xu , Pascal Fua

Large Language Models (LLMs) are widely used in critical fields such as healthcare, education, and finance due to their remarkable proficiency in various language-related tasks. However, LLMs are prone to generating factually incorrect…

Large Language Models (LLMs) are advanced Artificial Intelligence (AI) systems that have undergone extensive training using large datasets in order to understand and produce language that closely resembles that of humans. These models have…

软件工程 · 计算机科学 2023-08-10 Alessio Buscemi

Creating machines capable of understanding the world in 3D is essential in assisting designers that build and edit 3D environments and robots navigating and interacting within a three-dimensional space. Inspired by advances in language and…

计算机视觉与模式识别 · 计算机科学 2026-01-07 Aadarsh Sahoo , Vansh Tibrewal , Georgia Gkioxari

The advance of Artificial Intelligence (AI) is continuously reshaping the future 6G wireless communications. Particularly, the development of Large Language Models (LLMs) offers a promising approach to effectively improve the performance…

信息论 · 计算机科学 2025-03-10 Tianyue Zheng , Linglong Dai

Large Language Models (LLMs), through their contextualized representations, have been empirically proven to encapsulate syntactic, semantic, word sense, and common-sense knowledge. However, there has been limited exploration of their…

计算与语言 · 计算机科学 2023-10-12 Yi Ru Wang , Jiafei Duan , Dieter Fox , Siddhartha Srinivasa

3D object segmentation with Large Language Models (LLMs) has become a prevailing paradigm due to its broad semantics, task flexibility, and strong generalization. However, this paradigm is hindered by representation misalignment: LLMs…

计算机视觉与模式识别 · 计算机科学 2026-02-20 Zhuoxu Huang , Mingqi Gao , Jungong Han

Large language models (LLMs) can now generate physics practice problems in real time, yet the educational value of these items hinges on rapid, reliable post-generation vetting. In this exploratory study, we investigated which automated…

物理教育 · 物理学 2026-04-13 Tobias Geisler , Gerd Kortemeyer

New era has unlocked exciting possibilities for extending Large Language Models (LLMs) to tackle 3D vision-language tasks. However, most existing 3D multimodal LLMs (MLLMs) rely on compressing holistic 3D scene information or segmenting…

计算机视觉与模式识别 · 计算机科学 2025-07-23 Xiaoyan Wang , Zeju Li , Yifan Xu , Jiaxing Qi , Zhifei Yang , Ruifei Ma , Xiangde Liu , Chao Zhang

Multi-modal Large Language Models (MLLMs) exhibit impressive capabilities in 2D tasks, yet encounter challenges in discerning the spatial positions, interrelations, and causal logic in scenes when transitioning from 2D to 3D…

计算机视觉与模式识别 · 计算机科学 2025-01-15 Haomiao Xiong , Yunzhi Zhuge , Jiawen Zhu , Lu Zhang , Huchuan Lu

Recovering Computer-Aided Design (CAD) programs from 3D geometries is a widely studied problem. Recent advances in large language models (LLMs) have enabled progress in CAD program synthesis, but existing methods rely on supervised training…

计算机视觉与模式识别 · 计算机科学 2026-02-16 Yuanbo Li , Dule Shu , Yanying Chen , Matt Klenk , Daniel Ritchie