Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design....
Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or f...
Leveraging existing environment simulators and reward functions based on verifiable ground truth boosts task success rate, even with small models and small trai...
'Reinforcement learning gyms' train agents on the many low-level tasks that they must chain together to execute customer requests....
Robot friends collaborate to learn to fly a drone The post Deep Reinforcement Learning: The Actor-Critic Method appeared first on Towards Data Science....
Article URL: https://kywch.github.io/blog/2025/12/curriculum-learning-2048-tetris/ Comments URL: https://news.ycombinator.com/item?id=46445195 Points: 6 Comment...
Towards understanding if your agentic solution is actually better The post Agents Under the Curve AUC appeared first on Towards Data Science....
How to make LLMs reason with verifiable, step-by-step logic Part 2 The post Implementing Vibe Proving with Reinforcement Learning appeared first on Towards Data...
Introduction In machine learning, reinforcement learning RL is a paradigm where problem formulation matters as much as the algorithm itself. Unlike supervised...
Read more about Language Agent Tree Search Unifies Reasoning, Acti...
OpenAI is strengthening ChatGPT Atlas against prompt injection attacks using automated red teaming trained with reinforcement learning. This proactive discover-...
markdown !Cover image for “How I built AI model that plays Whot! card game”https://media2.dev.to/dynamic/image/width=1000,height=420,fit=cover,gravity=auto,form...
