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The determination of space layout is one of the primary activities in the schematic design stage of an architectural project. The initial layout planning defines the shape, dimension, and circulation pattern of internal spaces; which can…

Artificial Intelligence · Computer Science 2024-06-24 Zhipeng Li , Sichao Li , Geoff Hinchcliffe , Noam Maitless , Nick Birbilis

Personalized generation paradigms empower designers to customize visual intellectual properties with the help of textual descriptions by tuning or adapting pre-trained text-to-image models on a few images. Recent works explore approaches…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Yu Xu , Fan Tang , Juan Cao , Yuxin Zhang , Oliver Deussen , Weiming Dong , Jintao Li , Tong-Yee Lee

Generative AI can be used in multi-actor environments with purposes ranging from social science modeling to interactive narrative and AI evaluation. Supporting this diversity of use cases -- which we classify as Simulationist, Dramatist,…

Building explainable systems is a critical problem in the field of Natural Language Processing (NLP), since most machine learning models provide no explanations for the predictions. Existing approaches for explainable machine learning…

Computation and Language · Computer Science 2019-06-12 Hui Liu , Qingyu Yin , William Yang Wang

Large Language Models (LLMs) promise to accelerate discovery by reasoning across the expanding scientific landscape. Yet, the challenge is no longer access to information but connecting it in meaningful, domain-spanning ways. In materials…

Artificial Intelligence · Computer Science 2026-02-10 Isabella A. Stewart , Tarjei Paule Hage , Yu-Chuan Hsu , Markus J. Buehler

We introduce a continuous-time generative modeling framework, motivated by the Chow-Rashevskii theorem, that builds expressive flows from a small set of fixed vector fields and learned scalar controls. Instead of learning an unconstrained…

Machine Learning · Computer Science 2026-05-28 Peyman Morteza

Deep generative models like VAEs and diffusion models have advanced various generation tasks by leveraging latent variables to learn data distributions and generate high-quality samples. Despite the field of explainable AI making strides in…

Machine Learning · Computer Science 2025-12-22 Mengdan Zhu , Raasikh Kanjiani , Jiahui Lu , Andrew Choi , Qirui Ye , Liang Zhao

Efficient exploration remains a challenging problem in reinforcement learning, especially for those tasks where rewards from environments are sparse. A commonly used approach for exploring such environments is to introduce some "intrinsic"…

Machine Learning · Computer Science 2020-07-16 Neale Ratzlaff , Qinxun Bai , Li Fuxin , Wei Xu

In the combinatorial recommender systems, multiple items are fed to the user at one time in the result page, where the correlations among the items have impact on the user behavior. In this work, we model the combinatorial recommendation as…

Information Retrieval · Computer Science 2019-06-25 Fan Wang , Xiaomin Fang , Lihang Liu , Yaxue Chen , Jiucheng Tao , Zhiming Peng , Cihang Jin , Hao Tian

Using artificial intelligence (AI) to automatically test a game remains a critical challenge for the development of richer and more complex game worlds and for the advancement of AI at large. One of the most promising methods for achieving…

Artificial Intelligence · Computer Science 2022-09-02 Matthew Barthet , Ahmed Khalifa , Antonios Liapis , Georgios N. Yannakakis

Self-reflection enables language agents to iteratively refine solutions, yet often produces repetitive outputs that limit reasoning performance. Recent studies have attempted to address this limitation through various approaches, among…

Machine Learning · Computer Science 2026-03-02 Tianjun Yao , Yongqiang Chen , Yujia Zheng , Pan Li , Zhiqiang Shen , Kun Zhang

People grasp flexible visual concepts from a few examples. We explore a neurosymbolic system that learns how to infer programs that capture visual concepts in a domain-general fashion. We introduce Template Programs: programmatic…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 R. Kenny Jones , Siddhartha Chaudhuri , Daniel Ritchie

Recent advances in deep-research systems have demonstrated the potential for AI agents to autonomously discover and synthesize knowledge from external sources. In this paper, we introduce WebResearcher, a novel framework for building such…

Designers rely on visual search to explore and develop ideas in early design stages. However, designers can struggle to identify suitable text queries to initiate a search or to discover images for similarity-based search that can…

Human-Computer Interaction · Computer Science 2024-03-05 Kihoon Son , DaEun Choi , Tae Soo Kim , Young-Ho Kim , Juho Kim

Generative art is a rules-driven approach to creating artistic outputs in various mediums. For example, a fluid simulation can govern the flow of colored pixels across a digital display or a rectangle placement algorithm can yield a…

Neural and Evolutionary Computing · Computer Science 2024-07-30 Erik M. Fredericks , Denton Bobeldyk , Jared M. Moore

Recent advancements in Natural Language Processing (NLP) have led to the development of NLP-based recommender systems that have shown superior performance. However, current models commonly treat items as mere IDs and adopt discriminative…

Information Retrieval · Computer Science 2023-04-11 Jinming Li , Wentao Zhang , Tian Wang , Guanglei Xiong , Alan Lu , Gerard Medioni

Using tools from topology and functional analysis, we provide a framework where artificial neural networks, and their architectures, can be formally described. We define the notion of machine in a general topological context and show how…

Machine Learning · Computer Science 2022-11-30 Pietro Vertechi , Mattia G. Bergomi

Generative design, an AI-assisted technology for optimizing design through algorithmic processes, is propelling advancements across numerous fields. As the use of immersive environments such as Augmented Reality (AR) continues to rise,…

Human-Computer Interaction · Computer Science 2025-03-28 Sora Kang , Kaiwen Yu , Xinyi Zhou , Joonhwan Lee

Scientists often use meta-analysis to characterize the impact of an intervention on some outcome of interest across a body of literature. However, threats to the utility and validity of meta-analytic estimates arise when scientists average…

Human-Computer Interaction · Computer Science 2023-02-21 Alex Kale , Sarah Lee , Terrance Goan , Elizabeth Tipton , Jessica Hullman

In many contexts, creating mappings for gestural interactions can form part of an artistic process. Creators seeking a mapping that is expressive, novel, and affords them a sense of authorship may not know how to program it up in a signal…

Human-Computer Interaction · Computer Science 2021-06-17 Tim Murray-Browne , Panagiotis Tigas