arXiv:2602.03965v1 Announce Type: new Abstract: Latency anomalies, defined as persistent or transient increases in round-trip time (RTT), are common in residential Internet performance. When multiple users observe anomalies to the same destination, this may reflect shared infrastructure, routing behavior, or congestion. Inferring such shared behavior is challenging because anomaly magnitudes vary widely across devices, even within the same ISP and geographic area, and detailed network topology information is often unavailable. We study whether devices experiencing a shared latency […]

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Please, please, please stop using passkeys for encrypting user data Because users lose their passkeys all the time, and may not understand that their data has been irreversibly encrypted using them and can no longer be recovered. Tim Cappalli: To the wider identity industry: please stop promoting and using passkeys to encrypt user data. I’m begging you. Let them be great, phishing-resistant authentication credentials. Via lobste.rs Tags: security, usability, passkeys

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Self-supervised learning (SSL) faces a fundamental conflict between semantic understanding and image reconstruction. High-level semantic SSL (e.g., DINO) relies on global tokens that are forced to be location-invariant for augmentation alignment, a process that inherently discards the spatial coordinates required for reconstruction. Conversely, generative SSL (e.g., MAE) preserves dense feature grids for reconstruction but fails to produce high-level abstractions. We introduce STELLAR, a framework that resolves this tension by factorizing visual features into a low-rank product of semantic […]

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Explainable AI (XAI) has become critical as transformer-based models are deployed in high-stakes applications including healthcare, legal systems, and financial services, where opacity hinders trust and accountability. Transformers self-attention mechanisms have proven valuable for model interpretability, with attention weights successfully used to understand model focus and behavior (Xu et al., 2015); (Wiegreffe and Pinter, 2019). However, existing attention-based explanation methods rely on manually defined aggregation strategies and fixed attribution rules (Abnar and Zuidema, 2020a); (Chefer et al., 2021), […]

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arXiv:2603.08807v1 Announce Type: new Abstract: We consider a matching problem for time series with values in an arbitrary metric space, with the stretching penalty given by the Hellinger kernel. To optimize this matching, we introduce the Elastic Time Warping algorithm with a cubic computational complexity.

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arXiv:2601.20875v1 Announce Type: cross Abstract: The achievement of the 2030 Sustainable Development Goals (SDGs) is dependent upon strategic resource distribution. We propose a causal discovery framework using Panel Vector Autoregression, along with both country-specific fixed effects and PCMCI+ conditional independence testing on 168 countries (2000-2025) to develop the first complete causal architecture of SDG dependencies. Utilizing 8 strategically chosen SDGs, we identify a distributed causal network (i.e., no single ‘hub’ SDG), with 10 statistically significant Granger-causal relationships identified […]

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Credit fraud detection is a central problem in financial risk management. It is challenging due to complex relationships among transaction entities, strong coordination of fraudulent activities, and high levels of behavioral camouflage at the individual level. Traditional approaches mainly rely on features from independent samples. They often fail to represent multi-entity interaction structures effectively. From a relational modeling perspective, this study investigates a graph neural network-based method for credit fraud detection. The method represents transaction entities and their […]

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arXiv:2603.25944v1 Announce Type: new Abstract: Large language models show promise for legal applications, but deploying frontier models raises concerns about cost, latency, and data privacy. We evaluate whether sub-10B parameter models can serve as practical alternatives by testing nine models across three legal benchmarks (ContractNLI, CaseHOLD, and ECtHR) using five prompting strategies (direct, chain-of-thought, few-shot, BM25 RAG, and dense RAG). Across 405 experiments with three random seeds per configuration, we find that a Mixture-of-Experts model activating only 3B […]

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The Markup, now a part of CalMatters, uses investigative reporting, data analysis, and software engineering to challenge technology to serve the public good. Sign up for Klaxon, a newsletter that delivers our stories and tools directly to your inbox. U.S. Customs and Border Protection is trying to build AI-powered border surveillance systems that automate the process of scanning people trying to cross into the U.S., an effort that experts say could push migrants to take more perilous routes […]

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