In this quiz, you’ll test your understanding of the tutorial Data Management With Python, SQLite, and SQLAlchemy. By working through this quiz, you’ll revisit how Python, SQLite, and SQLAlchemy work together to give your programs reliable data storage. You’ll also check your grasp of primary and foreign keys, SQL operations, and the SQLAlchemy models that let you work with your data as Python objects. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & […]

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Time series classification (TSC) is dominated by a two-stage paradigm: train a feature encoder — either from scratch on the target dataset or via pretraining on large corpora — and then fit a task-specific classifier on top. While effective, this decoupling optimizes representation learning independently of the classification objective, requires per-dataset training, and prevents the model from exploiting label information during inference. We introduce TimEE, a 4.5M-parameter foundation model for end-to-end TSC via in-context learning. Given a labeled […]

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Synthetic Sciences has released OpenScience, an open-source AI workbench for scientific research. It is licensed under Apache 2.0 and runs on your own infrastructure. The research team frames it as an open alternative to Anthropic’s Claude Science, launched in late June 2026. The pitch is direct. Scientific AI tooling should not be owned by one vendor. OpenScience keeps the workflow open, the models swappable, and the data local. It is an independent project, not affiliated with or endorsed […]

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arXiv:2601.22196v1 Announce Type: new Abstract: In 2024, the Linux kernel became its own Common Vulnerabilities and Exposures (CVE) Numbering Authority (CNA), formalizing how kernel vulnerabilities are identified and tracked. We analyze the anatomy and dynamics of kernel CVEs using metadata, associated commits, and patch latency to understand what drives patching. Results show that severity and Common Vulnerability Scoring System (CVSS) metrics have a negligible association with patch latency, whereas kernel recency is a reasonable predictor in survival models. […]

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Most de-identification tools are stateless. They scan a document, remove identifiers, done. No memory of what came before, no awareness of risk accumulating over time. That works fine for isolated records. It breaks down in streaming systems where the same patient appears across hundreds of events over time. I framed this as a control problem instead. The system maintains a per-subject exposure state and computes rolling re-identification risk as new events arrive. When risk crosses a threshold, the […]

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arXiv:2605.23145v1 Announce Type: new Abstract: Individual fairness, the notion that “similar individuals should be treated similarly,” provides a strong and flexible fairness guarantee for algorithmic decision makers. However, a barrier to implementing individual fairness in practice is the difficulty of learning the similarity metric over individuals. In this work, we present an algorithm for learning a Mahalanobis similarity metric from triplet queries of the form “is individual $i$ more similar to individual $j$ or $k$?” We work in […]

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The increasing reliance on human preference feedback to judge AI-generated pseudo labels has created a pressing need for principled, budget-conscious data acquisition strategies. We address the crucial question of how to optimally allocate a fixed annotation budget between ground-truth labels and pairwise preferences in AI. Our solution, grounded in semi-parametric inference, casts the budget allocation problem as a monotone missing data framework. Building on this formulation, we introduce Preference-Calibrated Active Learning (PCAL), a novel method that learns the […]

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arXiv:2601.00235v1 Announce Type: new Abstract: Automated detection of software vulnerabilities remains a critical challenge in software security. Log4j is an industrial-grade Java logging framework listed as one of the top 100 critical open source projects. On Dec. 10, 2021 a severe vulnerability Log4Shell was disclosed before being fully patched with Log4j2 version 2.17.0 on Dec. 18, 2021. However, to this day about 4.1 million, or 33 percent of all Log4j downloads in the last 7 days contain vulnerable […]

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arXiv:2606.04380v1 Announce Type: new Abstract: Forecast reconciliation usually starts from a fixed measurement system and asks how forecasts should be projected onto a coherent space. We ask a different question: which additional linear measurements should be forecast and included in the reconciliation system? We propose REGAIN, a reconciliation-gain framework that learns normalized auxiliary directions, forecasts the induced series with a frozen forecasting oracle, and selects directions by their target-weighted loss reduction after augmented generalized least-squares reconciliation. Unlike variance-based […]

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