Arhan Jain
317 posts
🧵(6) DROID Eval CoVer-VLA achieves 14% gains in task progress and 9% in success rate on the challenging red-team PolaRiS benchmark. In the pan cleaning task, π₀.₅ shows incorrect intent, grasping the pan handle. In contrast, CoVer-VLA correctly uses sponge to scrub the pan.
Introducing CoVer-VLA💫— a contrastive verifier + hierarchical test-time scaling framework for VLAs! - Lightweight 1B verifier 🧠 - Outperforms π₀ & π₀.₅ 🦾 - Trained on Bridge & DROID 🤖 Turns out scaling verification > scaling policy learning for VLA alignment! 🧵👇 🌐 Website: cover-vla.github.io 📄 Paper: arxiv.org/abs/2602.12281 🤗 Models: huggingface.co/cover-vla 💻 Code: github.com/cover-vla/cove…
Evaluating robot policies is hard. Ideally, instead of testing every new policy on a real robot, you could test in simulation; but simulations rarely correlate well with real-world performance. In order to make good, useful simulations, you need to spend a great deal of time and effort. That’s where PolaRiS comes in: it’s a toolkit that lets you take a short video of a real scene and turn it into a high-fidelity simulation. It provides what you need to build a good evaluation environment, and it “ships” with off-the-shelf environments that already show strong sim-to-real correlation, meaning that they can be used to inform policy performance. @prodarhan and @KarlPertsch join us to talk about what they have built, why, and how you can use it. Watch Episode #62 of RoboPapers, with @chris_j_paxton and @DJiafei, now!
Evaluating robot policies is hard. Ideally, instead of testing every new policy on a real robot, you could test in simulation; but simulations rarely correlate well with real-world performance. In order to make good, useful simulations, you need to spend a great deal of time and effort. That’s where PolaRiS comes in: it’s a toolkit that lets you take a short video of a real scene and turn it into a high-fidelity simulation. It provides what you need to build a good evaluation environment, and it “ships” with off-the-shelf environments that already show strong sim-to-real correlation, meaning that they can be used to inform policy performance. @prodarhan and @KarlPertsch join us to talk about what they have built, why, and how you can use it. Watch Episode #62 of RoboPapers, with @chris_j_paxton and @DJiafei, now!
Evaluating robot policies is hard. Ideally, instead of testing every new policy on a real robot, you could test in simulation; but simulations rarely correlate well with real-world performance. In order to make good, useful simulations, you need to spend a great deal of time and effort. That’s where PolaRiS comes in: it’s a toolkit that lets you take a short video of a real scene and turn it into a high-fidelity simulation. It provides what you need to build a good evaluation environment, and it “ships” with off-the-shelf environments that already show strong sim-to-real correlation, meaning that they can be used to inform policy performance. @prodarhan and @KarlPertsch join us to talk about what they have built, why, and how you can use it. Watch Episode #62 of RoboPapers, with @chris_j_paxton and @DJiafei, now!
Evaluating robot policies is hard. Ideally, instead of testing every new policy on a real robot, you could test in simulation; but simulations rarely correlate well with real-world performance. In order to make good, useful simulations, you need to spend a great deal of time and effort. That’s where PolaRiS comes in: it’s a toolkit that lets you take a short video of a real scene and turn it into a high-fidelity simulation. It provides what you need to build a good evaluation environment, and it “ships” with off-the-shelf environments that already show strong sim-to-real correlation, meaning that they can be used to inform policy performance. @prodarhan and @KarlPertsch join us to talk about what they have built, why, and how you can use it. Watch Episode #62 of RoboPapers, with @chris_j_paxton and @DJiafei, now!
Full episode dropping soon! Geeking out with @prodarhan @KarlPertsch on PolaRiS: Scalable Real-to-Sim Evaluations for Generalist Robot Policies polaris-evals.github.io Co-hosted by @chris_j_paxton @DJiafei
