It turns out you can just take an off-the-shelf VLM and fine-tune it directly to output robot actions *as text* and it performs better than/as-good-as all the more complex model architectures… Check out the paper!

Wonderful to be back from #CVPR2026, and excited to share the release of our follow-up work: VoLo: A Physical Orchestrator for Open-Vocabulary Long-Horizon Manipulation VoLo introduces the idea of a physical orchestrator for open-vocabulary, long-horizon manipulation. Our goal is to move toward robots that can reason, plan, act, monitor, and recover by adaptively using VLA/WAMs, vision models, and action primitives as tools. We introduce three main contributions: 🤖 VoLoAgent — a physical orchestrator that plans, monitors, and recovers by adaptively using, halting, and redirecting robot actions with tools. 📊 RoboVoLo — a high-fidelity benchmark with 126 open-vocabulary long-horizon manipulation tasks spanning common sense, memory/state tracking, complex references, and world knowledge. 📈 A large-scale empirical study comparing action models, code-as-policy systems, TAMP-style systems, and ablations of the VoLoAgent orchestrator, complemented by real-robot experiments. This work was done during my internship at @NVIDIA and would not have been possible without my brilliant collaborators: Hugo Hadfield, Alexander Zook, @mikacuy, @luke_ch_song, @erwincoumans, @xuningy, Faisal Ladhak, @qu_1006, @BirchfieldStan, Jonathan Tremblay, and @robovalts. Huge thanks to everyone! 🔗 Project: chicychen.github.io/VoLo/ 🔗 Previous work, SpaceTools: spacetools.github.io/ #Robotics #EmbodiedAI #VisionLanguageModels #VLAModels #RobotLearning #NVIDIA #CVPR2026 #LongHorizonManipulation #AI #ComputerVision

Evaluation is a critical bottleneck in building robot foundation models. Check out our latest work RoboLab, led by @xuningy, which addresses this exact challenge. Its a high-fidelity simulation environment for testing these models. A truly generalist policy should be able to complete these tasks zero-shot, and this benchmark highlights exactly how far we still have to go. More info 👇

RoboLab comes with RoboLab-120 — a curated, diverse benchmark of 120 tasks to get started. Set up and run in <20 min. (6/6) Try it out 👇 🌐 research.nvidia.com/labs/srl… 📄 arxiv.org/abs/2604.09860 💻 github.com/NVLabs/RoboLab

When every generalist robot model scores 95% on a benchmark, the numbers become meaningless. What if we built a photorealistic benchmark that never saturates and can generate new scenes and tasks with AI Workflows in minutes? We introduce RoboLab! 🧵(1/6)

Check out Yash Narang's GTC talk today where he will highlight some of our work on GPU-accelerated multi-arm manipulation planning! nvidia.com/gtc/session-catal… github.com/NVlabs/ScheduleSt…

Happy to share that the code for VLA-0 is out now: github.com/NVlabs/vla0 Given its simplicity, it’s a great starting point to try out VLAs!

Today we have open sourced our training code for vla0, our state of the art VLA with zero modifications. Have a go with it here github.com/NVlabs/vla0

Huge thanks to my incredible collaborators: @HugoHadfield1, Xuning Yang, Valts Blukis, Fabio Ramos And the amazing teams at NVIDIA @NVIDIARobotics @NVIDIAAI @NVIDIAEmbedded If you're excited about simple, effective approaches to VLAs: 💻 Code: github.com/NVlabs/vla0 (Coming soon!) 🌐 Page: vla0.github.io 📄 Paper: arxiv.org/abs/2510.13054

What's the right architecture for a VLA? VLM custom action heads (π₀)? VLM with special discrete action tokens (OpenVLA)? Custom design on top of the VLM (OpenVLA-OFT)? Or... VLM with ZERO modifications? Just predict action as text. The results will surprise you. VLA-0: Outperforms π₀, GR00T-N1, MolmoAct, SmolVLA. With ZERO changes to the VLM. 🧵⬇️

I feel the pain #students

Built a little automated N'th order derivative package yesterday afternoon as I got a bit tired of dealing with nasty time series data with noisy/missing values and people seem to like it :) github.com/hugohadfield/kalm…

Cool project by @EricWieser to formalize all of the Matrix Cookbook in Lean! github.com/eric-wieser/lean-…

Now with blog post write up! hh409.user.srcf.net/blog/len…