Machine Learning

[2604.16399] IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software Development

Abstract page for arXiv paper 2604.16399: IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework fo...

[2603.09117] Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards

Abstract page for arXiv paper 2603.09117: Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Ve...

[2602.11084] GRASP: group-Shapley feature selection for patients

Abstract page for arXiv paper 2602.11084: GRASP: group-Shapley feature selection for patients

[2604.04996] Learning-Based Multi-Criteria Decision Making Model for Sawmill Location Problems

Abstract page for arXiv paper 2604.04996: Learning-Based Multi-Criteria Decision Making Model for Sawmill Location Problems

[2604.04988] Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression

Abstract page for arXiv paper 2604.04988: Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression

[2604.04987] Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling

Abstract page for arXiv paper 2604.04987: Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling

[2604.04986] Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic with an adaptive reduced-order model

Abstract page for arXiv paper 2604.04986: Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic ...

[2604.04983] Territory Paint Wars: Diagnosing and Mitigating Failure Modes in Competitive Multi-Agent PPO

Abstract page for arXiv paper 2604.04983: Territory Paint Wars: Diagnosing and Mitigating Failure Modes in Competitive Multi-Agent PPO

[2604.04971] A Theory-guided Weighted $L^2$ Loss for solving the BGK model via Physics-informed neural networks

Abstract page for arXiv paper 2604.04971: A Theory-guided Weighted $L^2$ Loss for solving the BGK model via Physics-informed neural networks

Anthropic's latest AI model identifies 'thousands of zero-day vulnerabilities' in 'every major operating system and every major web browser' — Claude Mythos Preview sparks race to fix critical bugs, some unpatched for decades

Thinking small: How small language models could lessen the AI energy burden

Anthropic says its most powerful AI cyber model is too dangerous to release publicly — so it built Project Glasswing

China is copying U.S. AI models — American companies say it is costing them billions of dollars

Rival U.S. firms are sharing information to detect so-called adversarial distillation attempts that violate their terms of service.

Continuous Knowledge Transfer Between Claude and Codex

For the last 8 months I've developed strictly using Claude Code, setting up context layers, hooks, skills, etc. But relying on one model ...

Anthropic says its latest AI model is too powerful for public release and that it broke containment during testing

Claude on Claude

The Story of Anthropic’s Latest Controversies Regarding the Business of Its Prized Creation… As Told by the Thing Itself. Editor’s note: ...

This OpenClaw paper shows why agent safety is an execution problem, not just a model problem

Paper: https://arxiv.org/abs/2604.04759 This OpenClaw paper is one of the clearest signals so far that agent risk is architectural, not j...

"Authoritarian Parents In Rationalist Clothes": a piece I wrote in December about alignment

Posted today in light of the Claude Mythos model card release. Originally I wrote this for r/ControlProblem but realized it was getting o...

[D] Your Agent, Their Asset: Real-world safety evaluation of OpenClaw agents (CIK poisoning raises attack success to ~64–74%)

Paper: https://arxiv.org/abs/2604.04759 This paper presents a real-world safety evaluation of OpenClaw, a personal AI agent with access t...

Anthropic debuts preview of powerful new AI model Mythos in new cybersecurity initiative

The new model will be used by a small number of high-profile companies to engage in defensive cybersecurity work.

I can't help rooting for tiny open source AI model maker Arcee | TechCrunch

Arcee is a tiny 26-person U.S. startup that built a high-performing, massive, open source LLM. And it's gaining popularity with OpenClaw ...

We have an AI agent fragmentation problem

Every AI agent works fine on its own — but the moment you try to use more than one, everything falls apart. Different runtimes. Different...

Using AI properly

AI is a tool. Period. I spent decades asking forums for help in writing HTML code for my website. I wanted my posts to self-scroll to a p...