arXiv:2602.10142v1 Announce Type: new Abstract: Smart Voice Assistants (SVAs) are deeply embedded in the lives of youth, yet the mechanisms driving the privacy-protective behaviors among young users remain poorly understood. This study investigates how Canadian youth (aged 16-24) negotiate privacy with SVAs by developing and testing a structural model grounded in five key constructs: perceived privacy risks (PPR), perceived benefits (PPBf), algorithmic transparency and trust (ATT), privacy self-efficacy (PSE), and privacy-protective behaviors (PPB). A cross-sectional survey of N=469 […]

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Large language models (LLMs) offer one of the most interesting opportunities for developing more efficient training methods. A few weeks ago, the NeurIPS 2023 LLM Efficiency Challenge launched to focus on efficient LLM finetuning, and this guide is a short walkthrough explaining how to participate in this competition. This article covers everything you need to know, from setting up the coding environment to making the first submission.

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The electric vehicle routing problem with time windows (EVRPTW) is a complex optimization problem in sustainable logistics, where routing decisions must minimize total travel distance, fleet size, and battery usage while satisfying strict customer time constraints. Although deep reinforcement learning (DRL) has shown great potential as an alternative to classical heuristics and exact solvers, existing DRL models often struggle to maintain training stability-failing to converge or generalize when constraints are dense. In this study, we propose a curriculum-based […]

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arXiv:2407.11518v2 Announce Type: replace Abstract: In this paper, we present a new ensemble-based filter method by reconstructing the analysis step of the particle filter through a transport map, which directly transports prior particles to posterior particles. The transport map is constructed through an optimization problem described by the Maximum Mean Discrepancy loss function, which matches the expectation information of the approximated posterior and reference posterior. The proposed method inherits the accurate estimation of the posterior distribution from particle […]

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IEEE 802.11be (Wi-Fi 7) extends wireless network capability through wider channels, higher-order modulation, and tri-band operation; however, realised indoor performance is strongly governed by propagation constraints. This study , therefore, presents a controlled empirical assessment of Wi-Fi 7 behaviour in a multi-storey university building, examining throughput and received signal strength across 2.4-, 5-, and 6 GHz bands using a single-link radio propagation measurement. Six experimental scenarios were designed to isolate dominant indoor impairments, including distance variation, wall penetration, […]

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Tell Us A Bit About Yourself I’m Saaniya Chugh, a Senior Technical Consultant at ServiceNow with a background in IT service management, digital transformation, and AI-driven automation. Over the last decade, I’ve worked across consulting, strategy, and leadership roles, helping organizations harness technology in meaningful ways. Alongside my professional journey, I’m passionate about writing and storytelling especially making complex ideas in ITSM and AI accessible to everyone. I’ve published thought pieces, contributed to HackerNoon, and recently authored a […]

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arXiv:2603.24768v1 Announce Type: new Abstract: The engineering design research community has studied agentic AI systems that use Large Language Model (LLM) agents to automate the engineering design process. However, these systems are prone to some of the same pathologies that plague humans. Just as human designers, LLM design agents can fixate on existing paradigms and fail to explore alternatives when solving design challenges, potentially leading to suboptimal solutions. In this work, we propose (1) a novel Self-Regulation Loop […]

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