Constrained Reinforcement Learning (CRL) aims to optimize decision-making policies under constraint conditions, making it highly applicable to safety-critical domains such as autonomous driving, robotics, and power grid management. However, existing robust CRL approaches predominantly focus on single-step perturbations and temporally independent adversarial models, lacking explicit modeling of robustness against temporally coupled perturbations. To tackle these challenges, we propose TCRL, a novel temporal-coupled adversarial training framework for robust constrained reinforcement learning (TCRL) in worst-case scenarios. First, TCRL introduces a […]

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Your PR descriptions are training data for your future self, and for every agent after you. TL;DR: Improve the AI tools, rules, skills, and workflows you use in every pull request so your team and future agents can learn, reproduce, and improve on every change. Common Mistake ❌ You write clean code. The AI helps you ship fast after it understands all your context, and you merge the PR. You write “Fix bug” as the description. Two weeks later, […]

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Teams researching code quality and security alternatives to SonarQube are rarely looking for another dashboard. They want more relevant findings, faster remediation, less tool sprawl, and a workflow developers will continue using after the initial rollout. SonarQube remains a capable benchmark. Its current platform analyzes bugs, code smells, vulnerabilities, security hotspots, and architecture issues across the IDE, pull requests, and CI/CD pipelines. It also provides quality profiles, quality gates, secrets detection, SAST, and—through Advanced Security—software composition analysis. The […]

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arXiv:2602.15071v1 Announce Type: new Abstract: “Intangible Victory” is an audiovisual installation in the form of the intangible being of the Victory of Samothrace that uses interactive digital media. Specifically, through this installation, we redefine the visual symbolism of the ancient sculpture, paying attention to time as a wear factor (entropy) and the special importance of the void as an absence of the sculptural form. Emptiness completes the intangible essence of the sculpture in the field of symbolism as […]

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We present a geometric framework for Reinforcement Learning (RL) that views policies as maps into the Wasserstein space of action probabilities. First, we define a Riemannian structure induced by stationary distributions, proving its existence in a general context. We then define the tangent space of policies and characterize the geodesics, specifically addressing the measurability of vector fields mapped from the state space to the tangent space of probability measures over the action space. Next, we formulate a general […]

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arXiv:2601.22358v1 Announce Type: new Abstract: Movable signals have emerged as a third approach to enable smart radio environments (SREs), complementing reconfigurable intelligent surfaces (RISs) and flexible antennas. This paper investigates their potential to enhance multi-user wireless systems. Focusing on two-user systems, we characterize the capacity regions of the multiple access channel (MAC) and broadcast channel (BC). Interestingly, movable signals can dynamically adjust the operating frequency to orthogonalize the user channels, thereby significantly expanding the capacity regions. We also […]

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Two hours of my life spent assuming there was a GPU cluster somewhere running an image classifier. There wasn’t. It’s reading metadata. That’s it. And I shipped the same thing on forg.to in an afternoon with zero new dependencies and zero added cost. Here’s the actual story. Why forg.to needed this forg.to is where indie hackers and builders share their product journey. Real wins, real losses, real progress. As AI image generation got good, posts started showing up […]

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What is ELT? ELT is a widely used concept in the data engineering world and stands for Extract, Load, and Transform. Extract – The process of reading raw data from various sources such as mainframes, databases, files, or communication platforms like emails and chats. Load – Involves storing the extracted data into a target system, such as a database or cloud storage solutions like Amazon S3, Azure Blob Storage, or Google Cloud Storage (GCS). Transform – The step where raw data is […]

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Release: scan-for-secrets 0.1 I like publishing transcripts of local Claude Code sessions using my claude-code-transcripts tool but I’m often paranoid that one of my API keys or similar secrets might inadvertently be revealed in the detailed log files. I built this new Python scanning tool to help reassure me. You can feed it secrets and have it scan for them in a specified directory: uvx scan-for-secrets $OPENAI_API_KEY -d logs-to-publish/ If you leave off the -d it defaults to […]

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Can we find a network architecture for ML model training so as to optimize training loss (and thus, accuracy) in Split Federated Learning (SFL)? And can this architecture also reduce training delay and communication overhead? While accuracy is not influenced by how we split the model in ordinary, state-of-the-art SFL, in this work we answer the questions above in the affirmative. Recent Hierarchical SFL (HSFL) architectures adopt a three-tier training structure consisting of clients, (local) aggregators, and a […]

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