Machine Learning (ML)

Applied to Reducing LLM deception at scale with self-other overlap fine-tuning by Gunnar_Zarncke 3d ago

Applied to Observations on self-supervised Learning for vision by Dinkar Juyal 7d ago

Applied to Estimating the Probability of Sampling a Trained Neural Network at Random by Adam Scherlis 15d ago

Applied to Self-fulfilling misalignment data might be poisoning our AI models by TurnTrout 16d ago

Applied to How to Contribute to Theoretical Reward Learning Research by Joar Skalse 16d ago

Applied to Other Papers About the Theory of Reward Learning by Joar Skalse 16d ago

Applied to Defining and Characterising Reward Hacking by Joar Skalse 16d ago

Applied to Misspecification in Inverse Reinforcement Learning by Joar Skalse 16d ago

Applied to The Theoretical Reward Learning Research Agenda: Introduction and Motivation by Joar Skalse 16d ago

Applied to Technical comparison of Deepseek, Novasky, S1, Helix, P0 by Juliezhanggg 19d ago

Applied to The GDM AGI Safety+Alignment Team is Hiring for Applied Interpretability Research by Arthur Conmy 20d ago

Applied to From No Mind to a Mind – A Conversation That Changed an AI by parthibanarjuna s 1mo ago

Applied to What If AI Recognized Meaning? An Inquiry into "Resonant Recognition" by JD___ 1mo ago

Applied to DeepSeek-R1 for Beginners by Anton Razzhigaev 1mo ago

Applied to Sleeper agents appear resilient to activation steering by Lucy Wingard 1mo ago

Applied to Machine Unlearning in Large Language Models: A Comprehensive Survey with Empirical Insights from the Qwen 1.5 1.8B Model by Saketh Baddam 1mo ago

Applied to How do biological or spiking neural networks learn? by Dom Polsinelli 1mo ago