Reinforcement Learning
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DenoiseRL Trains Reasoning Models to Recover From Their Own Wrong Starts
DenoiseRL is a reinforcement learning method that trains reasoning models on something most pipelines throw away: wrong answers. Instead of leaning on a stronger teacher model for supervision, it learns directly from the failures of weak models, turning bad reasoning traces into training signal. ## Conditioning on mistakes The trick is to start the model… Continue reading
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MobileGym Runs Hundreds of Parallel Mobile-Agent Sims in the Browser
MobileGym is a browser-hosted simulation platform for training and evaluating mobile GUI agents — the agents that tap, swipe, and type through phone apps. Its bet is that you don’t need to replicate proprietary app backends to train an agent; you need fidelity in the interaction and a way to verify outcomes cheaply. ## Verifiable… Continue reading
