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Artificial intelligence (AI) technologies, and particularly deep learning systems, are traditionally the domain of large-scale cloud servers, which have access to high computational and energy resources. Nonetheless, in Internet-of-Things…

Signal Processing · Electrical Eng. & Systems 2022-07-26 Nir Shlezinger , Ivan V. Bajic

The rise of mobile devices equipped with numerous sensors, such as LiDAR and cameras, has spurred the adoption of multi-modal deep intelligence for distributed sensing tasks, such as smart cabins and driving assistance. However, the arrival…

Machine Learning · Computer Science 2024-11-01 Fenmin Wu , Sicong Liu , Kehao Zhu , Xiaochen Li , Bin Guo , Zhiwen Yu , Hongkai Wen , Xiangrui Xu , Lehao Wang , Xiangyu Liu

Recent advancements in large language models (LLMs) and their multimodal variants have led to remarkable progress across various domains, demonstrating impressive capabilities and unprecedented potential. In the era of ubiquitous…

Signal Processing · Electrical Eng. & Systems 2025-02-14 Jiawei Shao , Xuelong Li

Generative AI brings novel and impressive abilities to help people in everyday tasks. There are many AI workflows that solve real and complex problems by chaining AI outputs together with human interaction. Although there is an undeniable…

Human-Computer Interaction · Computer Science 2024-06-03 Tao Long , Katy Ilonka Gero , Lydia B. Chilton

Customising AI technologies to each user's preferences is fundamental to them functioning well. Unfortunately, current methods require too much user involvement and fail to capture their true preferences. In fact, to avoid the nuisance of…

Information Retrieval · Computer Science 2023-08-14 Marc Serramia , Natalia Criado , Michael Luck

Feature interaction is a core ingredient in ranking models for large-scale recommender systems, yet making it both expressive and efficiently scalable remains challenging. Exhaustive pairwise interaction is powerful but incurs quadratic…

Information Retrieval · Computer Science 2026-01-27 Kaiyuan Li , Yongxiang Tang , Wenzheng Shu , Yanxiang Zeng , Chao Wang , Yanhua Cheng , Xialong Liu , Peng Jiang

The widespread adoption of AI in industry is often hampered by its limited robustness when faced with scenarios absent from training data, leading to prediction bias and vulnerabilities. To address this, we propose a novel streaming…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yutian Zhang , Zhongyi Pei , Yi Mao , Chen Wang , Lin Liu , Jianmin Wang

In qualitative research, data transcription is often labor-intensive and time-consuming. To expedite this process, a workflow utilizing artificial intelligence (AI) was developed. This workflow not only enhances transcription speed but also…

Computation and Language · Computer Science 2025-04-22 Jakob Sponholz , Andreas Weilinghoff , Juliane Schopf

Workflow technology is widely used to facilitate the business process in enterprise information systems (EIS), and it has the potential to reduce design time, enhance product quality and decrease product cost. However, significant…

Software Engineering · Computer Science 2012-09-19 Tingyu Liu , Yalong Cheng , Zhonghua Ni

Stack Overflow is one of the most popular Programming Community-based Question Answering (PCQA) websites that has attracted more and more users in recent years. When users raise or inquire questions in Stack Overflow, providing related…

Computation and Language · Computer Science 2021-04-06 Jiayan Pei , Yimin Wu , Zishan Qin , Yao Cong , Jingtao Guan

Current systems for data-parallel, incremental processing and view maintenance over high-rate streams isolate the execution of independent queries. This creates unwanted redundancy and overhead in the presence of concurrent incrementally…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-15 Frank McSherry , Andrea Lattuada , Malte Schwarzkopf , Timothy Roscoe

In this paper, we focus on Dynamic Execution techniques that optimize the computation flow based on input. This aims to identify simpler problems that can be solved using fewer resources, similar to human cognition. The techniques discussed…

Machine Learning · Computer Science 2024-11-05 Haim Barad , Jascha Achterberg , Tien Pei Chou , Jean Yu

Generative models have shown great promise in collaborative filtering by capturing the underlying distribution of user interests and preferences. However, existing approaches struggle with inaccurate posterior approximations and…

Information Retrieval · Computer Science 2025-09-08 Chengkai Liu , Yangtian Zhang , Jianling Wang , Rex Ying , James Caverlee

Group activities are important behaviors in human society, providing personalized recommendations for groups is referred to as the group recommendation task. Existing methods can usually be categorized into two strategies to infer group…

Information Retrieval · Computer Science 2024-09-05 Jinfeng Xu , Zheyu Chen , Jinze Li , Shuo Yang , Hewei Wang , Edith C. -H. Ngai

Similarity search is a key operation in multimedia retrieval systems and recommender systems, and it will play an important role also for future machine learning and augmented reality applications. When these systems need to serve large…

Networking and Internet Architecture · Computer Science 2022-09-23 T. Si-Salem , G. Neglia , D. Carra

Modern digital applications extensively integrate Artificial Intelligence models into their core systems, offering significant advantages for automated decision-making. However, these AI-based systems encounter reliability and safety…

Machine Learning · Computer Science 2024-11-05 Marcos Barcina-Blanco , Jesus L. Lobo , Pablo Garcia-Bringas , Javier Del Ser

Artificial Intelligence (AI) systems are transforming critical sectors such as healthcare, finance, and transportation, enhancing operational efficiency and decision-making processes. However, their deployment in high-stakes domains has…

Computers and Society · Computer Science 2025-08-01 Diego Russo , Gian Marco Orlando , Valerio La Gatta , Vincenzo Moscato

The importance of contexts has been widely recognized in recommender systems for individuals. However, most existing group recommendation models in Event-Based Social Networks (EBSNs) focus on how to aggregate group members' preferences to…

Social and Information Networks · Computer Science 2020-06-17 Guoqiong Liao , Xiaomei Huang , Neal N. Xiong , Changxuan Wan

Generative AI, such as image generation models and large language models, stands to provide tremendous value to end-user programmers in creative and knowledge workflows. Current research methods struggle to engage end-users in a realistic…

Human-Computer Interaction · Computer Science 2023-12-29 Advait Sarkar , Ian Drosos , Rob Deline , Andrew D. Gordon , Carina Negreanu , Sean Rintel , Jack Williams , Benjamin Zorn

Generative AI models differ from traditional machine learning tools in that they allow users to provide as much or as little information as they choose in their inputs. This flexibility often leads users to omit certain details, relying on…

Computer Science and Game Theory · Computer Science 2026-05-13 Charlotte Park , Kate Donahue , Manish Raghavan
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