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ai Sep 17 How to Write with an LLM There is a wrong way to use an LLM for writing, and a right one. The wrong way is to let the model generate your prose. The right way is to write everything yourself, then hand the draft to a model and let it find the problems you... ai Sep 17 Show HN: Die With Me – Claude and Codex rate limits as AIM away messages Die With Me Turns AI Token Limits Into a Social Experience Running out of tokens used to be a solitary frustration. You hit your Claude Code limit mid-refactor, stared at the error message, and waited. Now there is an app that tur... ai Sep 17 A Zeroth-Order Paradigm for LLM Preference Alignment The Likelihood Displacement Problem in Preference Alignment Training large language models to follow human preferences has become a core bottleneck in shipping reliable AI systems. Reinforcement learning from human feedback (RLHF)... cybersecurity Sep 17 AgentLSD: Evaluating AI Security Agents Under Adversarial Task Contamination When Security Agents Meet Deceptive Environments AI agents that handle security tasks do not operate in clean, trustworthy environments. They browse web pages, parse source code, read log files, and inspect configuration output. E... ai Sep 17 Dreaming the Sound of Contact: Leveraging Video and Audio Generation for Zero-Shot Force-Aware Manipulation and Data Generation Why Generated Video Alone Fails at Contact-Rich Manipulation Video generation models have opened a new path for robot learning. Instead of teleoperating a robot hundreds of times to collect demonstrations, you can generate a video... machine learning Sep 17 Probabilistic Linear Explanations When a machine learning model denies someone a loan or flags a medical scan, the most natural question is "why?" Formal explainability has spent years trying to answer that question with mathematical rigor. The dominant approach f... machine learning Sep 17 Double descent is the principle of least action The double descent phenomenon is one of the most counterintuitive findings in modern machine learning. Train a model with a small number of parameters and test error falls as you add more, following the classical bias-variance cur... ai Sep 16 Breaking the 1.58-bit Barrier for Ternary LLMs Ternary large language models pack every weight into one of three values: -1, 0, or +1. The information-theoretic floor for storing those choices is about 1.585 bits per weight, and the standard five-trit packing scheme used in pr... ai Sep 16 Agentic Societies Need a Social Harness When AI Agents Talk to Each Other, They Need More Than a Protocol Imagine two AI agents, each working on behalf of a different person, trying to schedule a meeting. One has access to its principal's calendar. The other has access... cybersecurity Sep 16 You Shall Not Pass into Ring-0! A User Privacy-Friendly Anti-Cheat Architecture for Personal Computers Anti-Cheat Software Spies on Players. This Architecture Stops That. When you install a competitive game like Valorant or Fortnite, you also install kernel-level anti-cheat software. Riot Vanguard, Easy Anti-Cheat, BattlEye, and FA...