Does LLM RL post-training need to be on-policy?

LLM training on RTX 5090

GPT-6 Astra test 4/n Prompt: "Implement pen spinning with... a dexterous hand. Use Isaac Lab for RL training, use the Sharpa hand, and create the pen mesh yourself. Give me a trained RL policy and a visualization video. You are free to search the web and download papers or anything else you need." After running autonomously for a day and a half (including training the policy), this is what we got: Credit: my student Chengyang Lishow more

Zombie robot RL policy

Does off-policy value-based RL scale? In LLMs, larger scale... predictably improves performance. Value-based RL learns from arbitrary data and is sample-efficient, but folk wisdom says it doesn't scale 🧵⬇️We show predictability for scaling value-based RL!show more

As a supporter of the open weights ecosystem, we're... proud to be a post-training partner for NVIDIA Nemotron. We post-train Nemotron models for customer use cases, de-risk mainline RL runs on our AC2 platform and training stack, and contribute aggregate workload statistics for inference benchmarking. This is how open models get better, and we're excited to keep working closely with NVIDIA AI.show more

Rare serious post on here but it need to... be said ❤️show more

Tutorial Time: Run any open-source LLM locally. Now we... will run an LLM on your M1/2 Mac. And its fast. All you need is moved to: @lmstudio let's get started. Good to be back. A threadshow more

training for RL 2027 🥰😋

Reinforcement learning should be able to improve upon behaviors... seen when training. In practice, RL agents often struggle to generalize to new long-horizon behaviors. Our new paper studies *horizon generalization*, the degree RL algorithms generalize to reaching distant goals. 1/show more

New project! Flow Policy Gradients for Robot Control tldr;... a simple online RL recipe for training and fine-tuning flow policies for robots co-led w/ Hongsuk Benjamin Choi:show more

Need my house to look like a RL store

How thick does ice need to be before you... can walk on it? 😭show more

Introducing autoresearch for arXiv papers: replicate and experiment on... any arXiv paper using an army of Claude/Codex agents For post-training, your agents can use Tinker to launch concurrent RL runs while you watch your experiment tree grow Try it out now on OpenResearch:show more

Training large models with RL typically runs on a... fixed homogeneous cluster of the latest accelerators for numerical stability and faster throughput. This throws away inference optimization work done for other vendors and generations, limits the capacity you can utilize, and is unnecessarily expensive. So we trained a model on agentic coding tasks using fully asynchronous RL and mixed-precision, mixed-accelerator samplers. With off-policy correction, training stayed stable through convergence, on par with homogeneous samplers, at a lower cost.show more

Does your bed board need to be replaced 😏

Nature does not always need venom to be terrifying.

ChatGPT uses your data for training its Large Language... Model (LLM). But now you can ask ChatGPT to NOT use data for training its model. Go to "Settings." Click on "Show" in front of "Data Controls." Turn off "Chat History and Training."show more

How does high-fidelity tactile simulation help robots nail the... last millimeter? We’re releasing VT-Refine, accepted to CoRL: a real-to-sim-to-real visuo-tactile policy using a GPU-parallel tactile sim for our piezoresistive skin FlexiTac. Then fine-tuning a diffusion policy with large-scale RL in simulation. Website: #CoRL2025 #RobotLearning #Sim2Realshow more

1/ RL for improving task success has made LLMs... remarkably capable. But what happens when the model fails? Turns out, training for graceful failure can be surprisingly tricky! Very excited to share our new paper: Training Language Models to Fail Gracefully 🧵show more