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Self-adaptive systems (SASs) are designed to handle changes and uncertainties through a feedback loop with four core functionalities: monitoring, analyzing, planning, and execution. Recently, generative artificial intelligence (GenAI),…

Software Engineering · Computer Science 2025-12-05 Jialong Li , Mingyue Zhang , Nianyu Li , Danny Weyns , Zhi Jin , Kenji Tei

In this research, we explore the efficacy and potential of Generative AI models, specifically focusing on their application in role-playing simulations exemplified through Spyfall, a renowned mafia-style game. By leveraging GPT-4's advanced…

Artificial Intelligence · Computer Science 2023-09-22 Munyeong Kim , Sungsu Kim

Foundation models can be disruptive for future AI development by scaling up deep learning in terms of model size and training data's breadth and size. These models achieve state-of-the-art performance (often through further adaptation) on a…

Artificial Intelligence · Computer Science 2022-12-20 Johannes Schneider

Testing new, innovative technologies is a crucial task for safety and acceptance. But how can new systems be tested if no historical real-world data exist? Simulation provides an answer to this important question. Classical simulation tools…

Machine Learning · Statistics 2020-09-04 Tom Peetz , Sebastian Vogt , Martin Zaefferer , Thomas Bartz-Beielstein

Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. As these systems scale, the bottleneck shifts away from raw…

Federated Learning (FL) has become an established technique to facilitate privacy-preserving collaborative training across a multitude of clients. However, new approaches to FL often discuss their contributions involving small deep-learning…

Machine Learning · Computer Science 2026-05-05 Herbert Woisetschläger , Alexander Isenko , Shiqiang Wang , Ruben Mayer , Hans-Arno Jacobsen

Federated Recommendation Systems (FRSs) offer a privacy-preserving alternative to traditional centralized approaches by decentralizing data storage. However, they face persistent challenges such as data sparsity and heterogeneity, largely…

Information Retrieval · Computer Science 2025-04-14 Zhiwei Li , Guodong Long , Chunxu Zhang , Honglei Zhang , Jing Jiang , Chengqi Zhang

Due to the increased number of parameters and data in the pre-trained model exceeding a certain level, a foundation model (e.g., a large language model) can significantly improve downstream task performance and emerge with some novel…

Artificial Intelligence · Computer Science 2023-11-13 Wensheng Gan , Shicheng Wan , Philip S. Yu

Machine Learning (ML) is profoundly reshaping the way researchers create, implement, and operate data-intensive software. Its adoption, however, introduces notable challenges for computing infrastructures, particularly when it comes to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-30 Lucio Anderlini , Giulio Bianchini , Diego Ciangottini , Stefano Dal Pra , Diego Michelotto , Rosa Petrini , Daniele Spiga

Large language models (LLMs) are catalyzing the development of autonomous AI research agents for scientific and engineering discovery. We present FM Agent, a novel and general-purpose multi-agent framework that leverages a synergistic…

Generative Artificial Intelligence (GenAI) is taking the world by storm. It promises transformative opportunities for advancing and disrupting existing practices, including healthcare. From large language models (LLMs) for clinical note…

Artificial Intelligence · Computer Science 2025-10-29 Gang Chen , Changshuo Liu , Gene Anne Ooi , Marcus Tan , Zhongle Xie , Jianwei Yin , James Wei Luen Yip , Wenqiao Zhang , Jiaqi Zhu , Beng Chin Ooi

The rapid advancements in Generative AI and Large Language Models promise to transform the way research is conducted, potentially offering unprecedented opportunities to augment scholarly workflows. However, effectively integrating AI into…

Synthetic data generation has emerged as a crucial topic for financial institutions, driven by multiple factors, such as privacy protection and data augmentation. Many algorithms have been proposed for synthetic data generation but reaching…

Machine Learning · Computer Science 2024-05-13 Shinpei Nakamura-Sakai , Fadi Hamad , Saheed Obitayo , Vamsi K. Potluru

Federated Learning as a decentralized artificial intelligence (AI) solution solves a variety of problems in industrial applications. It enables a continuously self-improving AI, which can be deployed everywhere at the edge. However,…

Machine Learning · Computer Science 2022-05-24 Nico Weber , Patrick Holzer , Tania Jacob , Enislay Ramentol

Integrating Foundation Models (FMs) into recommendation systems is an emerging and promising research direction. However, centralized paradigms face growing pressure from privacy concerns and strict regulatory requirements. Federated…

Machine Learning · Computer Science 2026-05-08 Zhiwei Li , Guodong Long , Chunxu Zhang , Honglei Zhang , Jing Jiang , Chengqi Zhang

Stellarators are a prospective class of fusion-based power plants that confine a hot plasma with three-dimensional magnetic fields. Typically framed as a PDE-constrained optimization problem, stellarator design is a time-consuming process…

Machine Learning · Computer Science 2025-12-15 Misha Padidar , Teresa Huang , Andrew Giuliani , Marina Spivak

Astronomy produces extremely large data sets from ground-based telescopes, space missions, and simulation. The volume and complexity of these rich data sets require new approaches and advanced tools to understand the information contained…

Instrumentation and Methods for Astrophysics · Physics 2014-02-25 Demitri Muna , Eric Huff

Foundation models (FMs), such as GPT-4 and AlphaFold, are reshaping the landscape of scientific research. Beyond accelerating tasks such as hypothesis generation, experimental design, and result interpretation, they prompt a more…

Machine Learning · Computer Science 2025-10-20 Fan Liu , Jindong Han , Tengfei Lyu , Weijia Zhang , Zhe-Rui Yang , Lu Dai , Cancheng Liu , Hao Liu

Saturn is a dual-purpose accelerator. It can be operated as a large-area flash x-ray source for simulation testing or as a Z-pinch driver especially for K-line x-ray production. In the first mode, the accelerator is fitted with three…

Accelerator Physics · Physics 2007-05-23 M. G. Mazarakis , R. B. Spielman , K. W. Struve , F. W. Long

AI for social impact (AI4SI) offers significant potential for addressing complex societal challenges in areas such as public health, agriculture, education, conservation, and public safety. However, existing AI4SI research is often…

Artificial Intelligence · Computer Science 2024-12-13 Yunfan Zhao , Niclas Boehmer , Aparna Taneja , Milind Tambe