We present a regularization-based approach for continual learning (CL) of fixed capacity convolutional neural networks (CNN) that does not suffer from the problem of catastrophic forgetting when learning multiple tasks sequentially. This method referred to as Group and Exclusive Sparsity based Continual Learning (GESCL) avoids forgetting of previous tasks by ensuring the stability of the CNN via a stability regularization term, which prevents filters detected as important for past tasks to deviate too much when learning a new […]

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The increasing availability of spatio-temporal tracking data has created new opportunities for analysing tactical behaviour in football. However, many existing approaches evaluate passes primarily through outcome-based metrics such as scoring probability or possession value, providing limited insight into how passes influence the defensive organisation of the opponent. This paper introduces a structural framework for analysing football passes based on their interaction with defensive structure. Using synchronised tracking/event data, we derive three complementary structural metrics, Line Bypass Score, Space […]

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arXiv:2602.09254v1 Announce Type: new Abstract: Bystander privacy in smart homes has been widely studied in Western contexts, yet it remains underexplored in non-Western countries such as China. In this study, we analyze 49 Chinese smart home apps using a mixed-methods approach, including privacy policy review, UX/UI evaluation, and assessment of Apple App Store privacy labels. While most apps nominally comply with national regulations, we identify significant gaps between written policies and actual implementation. Our traceability analysis highlights inconsistencies […]

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In 2026, China is establishing itself as a formidable competitor, achieving success with its Kimi AI tool. The advanced assistant developed by Moonshot AI, Kimi, has emerged as one of the most innovative AI products currently in the market. What makes Kimi AI’s Rise particularly noteworthy is its focus on long-context understanding, productivity, and agent-based workflows, which are areas where competition is intensifying globally. It serves as a strategic initiative to compete with ChatGPT and Gemini because intelligent […]

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https://youtu.be/OKjCaqQgHoU?embedable=true As the wave of digital transformation sweeps across the globe, intelligent manufacturing has become the core engine driving high-quality growth in manufacturing. n However, on the path toward intelligence, enterprises face a wide range of challenges: data silos across multiple systems, complex scheduling dependencies, and delayed monitoring and alerting continue to emerge. This article explores how a leading manufacturing enterprise achieved a qualitative leap in its scheduling platform with Apache DolphinScheduler. The Era of Intelligent Manufacturing With […]

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arXiv:2602.13315v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities, yet they encounter significant computational bottlenecks due to the massive volume of visual tokens. Consequently, visual token pruning, which substantially reduces the token count, has emerged as a critical technique for accelerating MLLM inference. Existing approaches focus on token importance, diversity, or an intuitive combination of both, without a principled framework for their optimal integration. To address this issue, we first conduct a systematic […]

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arXiv:2603.03376v1 Announce Type: new Abstract: As V2X (Vehicle-to-Everything) technology becomes increasingly prevalent, the security of V2X networks has garnered growing attention worldwide. In North America, the IEEE 1609 series standards are primarily used, while Europe adopts the ETSI series standards, and China has also established its industry standard, YD/T 3957-2021, among others. Although these standards share some commonalities, they also exhibit differences. To achieve compatibility across these standards, analyzing their similarities and differences is a crucial issue. Therefore, […]

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arXiv:2601.02396v1 Announce Type: new Abstract: Recent advances in satellite technology have introduced a new frontier of wireless networking by establishing Low Earth Orbit (LEO) Satellite networks that work to connect difficult to reach areas and improve global connectivity. These novel advancements lack robust open-source simulation models that can highlight potential bottlenecks or potential wasted resources, wasting terrestrial users and the companies that provide these networks time and money. To that end, we propose SLASh, a highly-customizable satellite network […]

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arXiv:2312.16819v4 Announce Type: replace-cross Abstract: We consider the optimization problem associated with training two-layer ReLU networks with (d) inputs under the squared loss, where the labels are generated by a target network. Recent work has identified two distinct classes of infinite families of minima: one whose training loss vanishes in the high-dimensional limit, and another whose loss remains bounded away from zero. The latter family is empirically avoided by stochastic gradient descent, hence emph{hidden}, motivating the search for […]

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