Articles tagged
reinforcement-learning
14 articles
ClawGUI: A Full-Stack Open-Source Pipeline for GUI Agents
ClawGUI unifies online RL training, reproducible evaluation, and real-device deployment of GUI agents into one open-source pipeline — and shows a 2B model trained inside it can beat 72B untrained baselines on MobileWorld.
SAGE: Your Reasoning Model Knows When to Stop Thinking — You Just Won't Let It
SAGE scores reasoning paths by cumulative log-probability instead of next-token probability, letting models stop thinking 40-50% earlier at equal or better accuracy.
Green-VLA: One AI Brain for All Robots
Green-VLA trains one policy for humanoids, mobile manipulators and fixed arms across five stages and 3,000 hours of demos, hitting state of the art on CALVIN ABC-D.
AI Co-Scientist: Teaching Models to Write Research Plans Better Than Humans
Rubrics mined from papers turn a frozen grader into an RL reward; experts preferred the generated research plans 70% over baseline and 52% over published ones.
DIALTREE‑RPO — a simple guide to 'Tree‑based Dialogue Reinforced Policy Optimization'
Friendly explanation of 'Tree‑based Dialogue Reinforced Policy Optimization for Red‑Teaming Attacks' — with examples and LaTeX formulas.
Attention as a Compass – Teaching Reasoning Models to Explore Smarter
AttnRL uses a model's own attention to pick branching points in process-supervised RL, beating GRPO and TreeRL by 1.8 points on math while cutting training time 8%.
Quantum Trading – AI and Quantum Computing in Investing
A QLSTM forecaster plus a QA3C agent trade USD/TWD with just 244 parameters, returning 11.87% over 2020-2025 at 0.92% max drawdown versus classical A3C's 11.42%.
Reinforcement Learning in Pinterest Ads – DRL-PUT in action!
DRL-PUT replaces Pinterest's hand-tuned ad ranking weights with a policy network picking utility weights per request; A/B tests show CTR up 9.7%, LC-CTR up 7.7%.
Uczenie ze Wzmocnieniem w Reklamach na Pinterest – jak DRL-PUT zmienia grę / Reinforcement Learning in Pinterest Ads – How DRL-PUT Changes the Game
Pinterest's DRL-PUT learns the weights of its ad ranking utility with policy gradients instead of tuning them by hand, lifting CTR by 9.7% and LC-CTR by 7.7%.
Look Inside Seamless Flow's Hyper-Efficient Training
Seamless Flow kills RL pipeline bubbles with a data plane and tag-driven GPU scheduling: up to 100% more throughput than VERL, and 23.0% to 45.8% on SWE-Bench.
Dynamic Fine-Tuning (DFT): How a Single Line of Code is Revolutionizing AI Training
Dynamic Fine-Tuning rescales each token loss by the inverse of its probability, a one-line change that beats SFT on generalization and rivals offline RL methods.
Optimizing Call Center Operations with Reinforcement Learning: PPO vs. Value Iteration
PPO beats classical Value Iteration at call routing in a discrete-event call centre simulation: shortest customer wait, least agent idle time, highest RL reward.
SOPHIA: Enhancing Slow‑Thinking in Large Vision‑Language Models
SOPHIA mixes on-policy visual grounding with off-policy reasoning chains and backward reward propagation, adding 8.5 points of average accuracy to InternVL3.0-38B.
The Role of AI in Managing Satellite Constellations
ConstellAI, an ESA project, uses reinforcement learning for routing in satellite mega-constellations, beating Dijkstra on delay and predicting bandwidth demand.