arXiv:2601.12252v1 Announce Type: new Abstract: WiFi-based 3D human pose estimation offers a low-cost and privacy-preserving alternative to vision-based systems for smart interaction. However, existing approaches rely on visual 3D poses as supervision and directly regress CSI to a camera-based coordinate system. We find that this practice leads to coordinate overfitting: models memorize deployment-specific WiFi transceiver layouts rather than only learning activity-relevant representations, resulting in severe generalization failures. To address this challenge, we present PerceptAlign, the first geometry-conditioned framework […]

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The Job-Shop Scheduling Problem (JSSP), under various forms of manufacturing uncertainty, has recently attracted considerable research attention. Most existing studies focus on parameter uncertainty, such as variable processing times, and typically adopt the actor-critic framework. In this paper, we explore a different but prevalent form of uncertainty in JSSP: structural uncertainty. Structural uncertainty arises when a job may follow one of several routing paths, and the selection is determined not by policy, but by situational factors (e.g., the […]

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Have you ever wondered what happens when you apply a filter in a DAX expression? Well, Today I will take you on a deep dive into this fascinating topic, with examples to help you learn something new and surprising. The post Take a Deep Dive into Filtering in DAX appeared first on Towards Data Science.

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arXiv:2602.17787v1 Announce Type: new Abstract: Generative model ecosystems increasingly operate as competitive multi-platform markets, where platforms strategically select models from a shared pool and users with heterogeneous preferences choose among them. Understanding how platforms interact, when market equilibria exist, how outcomes are shaped by model-providers, platforms, and user behavior, and how social welfare is affected is critical for fostering a beneficial market environment. In this paper, we formalize a three-layer model-platform-user market game and identify conditions for the […]

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Refactoring is essential for developing maintainable software. Using Large Language Models in software engineering is widespread, but compared to well-established domains such as code generation, reliable refactoring is still relatively underexplored. In this paper, we perform a broad analysis on the refactoring capabilities of small open-weight language models (SLMs) by evaluating 12 models on 3,453 Python programs. Our study focuses on the two defining aspects of refactoring: behavior preservation and code quality improvement. We evaluate these properties using […]

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I’m excited to share a major update to sklearn-diagnose – the open-source Python library that acts as an “MRI scanner” for your ML models (https://www.reddit.com/r/MachineLearning/s/EcMRYPVIDX) When I first released sklearn-diagnose, users could generate diagnostic reports to understand why their models were failing. But I kept thinking – what if you could talk to your diagnosis? What if you could ask follow-up questions and drill down into specific issues? Now you can! 🚀 🆕 What’s New: Interactive Diagnostic Chatbot […]

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arXiv:2601.02504v1 Announce Type: new Abstract: Debugging is a crucial skill in programming education and software development, yet it is often overlooked in CS curricula. To address this, we introduce an AI-powered debugging assistant integrated into an IDE. It offers real-time support by analyzing code, suggesting breakpoints, and providing contextual hints. Using RAG with LLMs, program slicing, and custom heuristics, it enhances efficiency by minimizing LLM calls and improving accuracy. A three-level evaluation – technical analysis, UX study, and […]

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A Blade Runner riff for a world where the lobster ships paid endpoints while humans still argue about the roadmap. The shift that matters for agent commerce – From “Crypto AI” to general AI Today, you can search the web all day and never see an invoice. n That happens because you are not the paying client. n The commerce runs through ads, affiliate deals, and platform incentives, so results often optimize for who pays, not for what […]

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