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Randomized controlled trials often do not represent the populations where decisions are made, and covariate shift across studies can invalidate standard IPD meta-analysis and transport estimators. We propose a placebo-anchored transport framework that treats source-trial outcomes as abundant proxy signals and target-trial placebo outcomes as scarce, high-fidelity gold labels to calibrate baseline risk. A low-complexity (sparse) correction anchors proxy outcome models to the target population, and the anchored models are embedded in a cross-fitted doubly robust learner, yielding […]

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Randomized controlled trials often do not represent the populations where decisions are made, and covariate shift across studies can invalidate standard IPD meta-analysis and transport estimators. We propose a placebo-anchored transport framework that treats source-trial outcomes as abundant proxy signals and target-trial placebo outcomes as scarce, high-fidelity gold labels to calibrate baseline risk. A low-complexity (sparse) correction anchors proxy outcome models to the target population, and the anchored models are embedded in a cross-fitted doubly robust learner, yielding […]

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The safety of large language models (LLMs) relies on alignment techniques such as reinforcement learning from human feedback (RLHF). However, recent theoretical analyses suggest that reinforcement learning-based training does not acquire new capabilities but merely redistributes the utilization probabilities of existing ones. In this study, we propose “compound jailbreaks” targeting OpenAI gpt-oss-20b, which exploit the generalization failures of alignment. This approach combines multiple attack techniques — each individually defended against — to saturate the instruction hierarchy maintenance process. […]

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Non-Exemplar Continual Graph Learning (NECGL) seeks to eliminate the privacy risks intrinsic to rehearsal-based paradigms by retaining solely class-level prototype representations rather than raw graph examples for mitigating catastrophic forgetting. However, this design choice inevitably precipitates feature drift. As a nascent alternative, Analytic Continual Learning (ACL) capitalizes on the intrinsic generalization properties of frozen pre-trained models to bolster continual learning performance. Nonetheless, a key drawback resides in the pronounced attenuation of model plasticity. To surmount these challenges, we […]

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In conversations about customer data, one question comes up again and again: if both CDPs and MDMs help create a more complete view of the customer, are they basically doing the same thing? It is an understandable question. After all, both technologies are often positioned around customer unification, identity resolution, and creating better visibility across systems. On the surface, they can sound very similar. But while CDPs and MDMs do overlap in some areas, they are not the […]

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Fetch, parse, and store is a web scraping order traditionally effective for most data pipelines. Up until recently, it was the dominating way to collect data, even at scale. With the rise of AI crawlers, however, more sophisticated anti-scraping strategies have become prevalent across the web. Websites have the right to defend themselves from malicious bots, but legitimate public data collection is affected as well. The traditional web scraping process must be rethought, with parsing becoming a part […]

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Most breach and attack simulation tools tell you what they found. VANGUARD tells you what it found, shows you the exact reasoning it used to find it, then writes the Elasticsearch detection rules you need to catch it next time – and deploys them automatically. Here’s how it works under the hood and what I learned building it. The Problem With Current BAS Tools Breach and Attack Simulation (BAS) tools like Cymulate, Pentera, and AttackIQ work by replaying […]

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Local LLMs are great – until you have to manage them on multiple machines. Ollama makes it easy to run models like Qwen, Mistral, and Gemma on consumer hardware, but most tools stop at “chat UI”. This tutorial shows how to build a production-ready admin dashboard for Ollama that runs on Android and Desktop with about 95% shared Kotlin Multiplatform code. You will: Build a Compose Multiplatform app with a shared UI layer for Android and Desktop. Implement […]

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How controlled DNS, segmented connectivity, and deterministic routing reduce financial risk in distributed pricing systems 1. The Missing Layer in Financial Automation Automated pricing systems are typically discussed in terms of: pricing algorithms competitive strategies machine learning models data pipelines However, at scale, a critical component is often overlooked: the network layer. In distributed pricing infrastructure, financial safety depends not only on how prices are calculated, but also on how reliably and predictably the system can: reach external […]

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