ACM Transactions on Intelligent Systems and Technology

Trustworthy artificial intelligence (TAI) has proven invaluable in curbing potential negative repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) emerges as a promising solution to safeguard personal information in ...

The emerging integration of Internet of Things (IoT) and AI has unlocked numerous opportunities for innovation across diverse industries. However, growing privacy concerns and data isolation issues have inhibited this promising advancement. Unfortunately, ...

In this article, we present an extensive survey of music information retrieval (MIR) research into music playlists. Our survey spans more than 20 years, and includes around 300 papers about playlists, with over 70 supporting sources. It is the first ...

Vision-and-language pre-training models have achieved impressive performance for image captioning. But most of them are trained with millions of paired image-text data and require huge memory and computing overhead. To alleviate this, we try to stand on ...

RGB-D cross-modal person re-identification (re-id) targets at retrieving the person of interest across RGB and depth image modalities. To cope with the modal discrepancy, some existing methods generate an auxiliary mode with either inherent properties of ...

Accurate prediction of citywide crowd activity levels (CALs), i.e., the numbers of participants of citywide crowd activities under different venue categories at certain time and locations, is essential for the city management, the personal service ...

In the realm of natural language processing, tasks like emotion recognition, irony detection, hate speech detection, offensive language identification, and stance detection are pivotal for understanding user-generated content. While several task-specific ...

Causality-informed machine learning has been proposed as an avenue for achieving many of the goals of modern machine learning, from ensuring generalization under domain shifts to attaining fairness, robustness, and interpretability. A key component of ...

This article presents the latest developments to ClaimBuster’s claim-spotting model, which tackles the critical task of identifying check-worthy claims from large streams of information. We introduce the first adversarially regularized, transformer-based ...

Non-rigid 3D shape correspondence aims to establish dense correspondences between two non-rigidly deformed 3D shapes. However, the variability and symmetry of non-rigid shapes usually lead to mismatches due to shape deformation, topological changes, or ...

Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this article, we propose a new FL framework, i.e., FedDUMAP, with three original ...

Understanding and accurately predicting cellular traffic data is vital for communication operators and device users, as it facilitates efficient resource allocation and ensures superior service quality. However, large-scale cellular traffic data ...

In logistics service, the delivery timely rate is a key experience indicator, which is highly essential to the competitive advantage of express companies. Prediction on it enables intervention on couriers with low predicted results in advance, thus ...

Affective feedback from social robots is a useful technique for communicating to people whether they are interacting “well” with the robot or not. However, some users, such as people with physical or cognitive difficulties, may not be able to interact in ...

Advancements in the Internet of Things (IoT) paradigm have greatly improved the quality of services in the electricity industry through the integration of smart energy distribution and dependable electric devices. Conspicuously, the current research ...

Recent methodologies have achieved good performance in objectively summarizing important information from fact-based datasets such as Extreme Summarization and CNN Daily Mail. These methodologies involve abstractive summarization, extracting the core ...

The anonymity and untraceability benefits of the dark web increased its popularity exponentially. The cost of these technical benefits is that such anonymity has created a suitable womb for illicit activity. Hence—in collaboration with cybersecurity ...

Recommendation explanations help to improve their acceptance by end users. Explanations come in many different forms. One that is of interest here is presenting an existing review of the recommended item as the explanation. The challenge is in selecting a ...

The illumination of images can significantly impact computer-vision applications such as image classification, multiple object detection, and tracking, leading to a significant decline in detection and tracking accuracy. Recent advancements in deep ...

Conventionally, federated learning aims to optimize a single objective, typically the utility. However, for a federated learning system to be trustworthy, it needs to simultaneously satisfy multiple objectives, such as maximizing model performance, ...

Temporal action detection, a critical task in video activity understanding, is typically divided into two stages: proposal generation and classification. However, most existing methods overlook the importance of information transfer among proposals during ...