正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

RoboMME Benchmarking and Understanding Memory for Robotic Generalist Policies paper:

AK

493,378 subscribers

11,808 次观看 • 6 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

🪞Symmetry helps shape RL policies. 🧠Can it also improve memory and task understanding? ✅We introduce Symmetry-Guided Memory Augmentation, combining structured experience augmentation with memory-based context inference to boost learning efficiency. 🔗

🪞Symmetry helps shape RL policies. 🧠Can it also improve memory and task understanding? ✅We introduce Symmetry-Guided Memory Augmentation, combining structured experience augmentation with memory-based context inference to boost learning efficiency. 🔗

Chenhao Li

14,863 次观看 • 5 个月前

Diffusion Policies and VLAs with Formal Safety Guarantees🛡️ We just released our new paper: “From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies” 📑Paper: 🌐Website:

Diffusion Policies and VLAs with Formal Safety Guarantees🛡️ We just released our new paper: “From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies” 📑Paper: 🌐Website:

Learning Systems and Robotics Lab (is hiring!)

20,356 次观看 • 9 个月前

We've solved another piece of the generalist gaming agent puzzle! Mario requires different skills than Pokemon: reactive navigation, spatial reasoning, and safe exploration rather than long-term memory and zero-sum reasoning. Check out our new paper on finetuning VLMs to beat Mario via PPO. 👇

We've solved another piece of the generalist gaming agent puzzle! Mario requires different skills than Pokemon: reactive navigation, spatial reasoning, and safe exploration rather than long-term memory and zero-sum reasoning. Check out our new paper on finetuning VLMs to beat Mario via PPO. 👇

Seth Karten

80,747 次观看 • 4 个月前

3D-R1 is out on Hugging Face Enhancing Reasoning in 3D VLMs for Unified Scene Understanding 3D-R1 is an open-source generalist model that enhances the reasoning of 3D VLMs for unified scene understanding

3D-R1 is out on Hugging Face Enhancing Reasoning in 3D VLMs for Unified Scene Understanding 3D-R1 is an open-source generalist model that enhances the reasoning of 3D VLMs for unified scene understanding

AK

34,729 次观看 • 1 年前

We’re releasing the RoboArena today!🤖🦾 Fair & scalable evaluation is a major bottleneck for research on generalist policies. We’re hoping that RoboArena can help! We provide data, model code & sim evals for debugging! Submit your policies today and join the leaderboard! :) 🧵

We’re releasing the RoboArena today!🤖🦾 Fair & scalable evaluation is a major bottleneck for research on generalist policies. We’re hoping that RoboArena can help! We provide data, model code & sim evals for debugging! Submit your policies today and join the leaderboard! :) 🧵

Karl Pertsch

111,628 次观看 • 1 年前

Excited to share our new work: StreamingVLM! 🚀 We tackle a major challenge for Vision-Language Models (VLMs): understanding infinite video streams in real-time without latency blowing up or running out of memory. Paper: Code:

Excited to share our new work: StreamingVLM! 🚀 We tackle a major challenge for Vision-Language Models (VLMs): understanding infinite video streams in real-time without latency blowing up or running out of memory. Paper: Code:

Guangxuan Xiao

92,141 次观看 • 10 个月前

Today, we publicly released RoboCasa365, a large-scale simulation benchmark for training and systematically evaluating generalist robot models. Built upon our original RoboCasa framework, it offers: • 2,500 realistic kitchen environments; • 365 everyday tasks (basic skills + long-horizon mobile manipulation); • Over 3,200 objects with many articulated fixtures/appliances. All are designed for fully controlled, reproducible benchmarking of robotic policies. Progress in robotic foundation models is real. But it’s still hard to answer basic questions like: How close are we to general-purpose autonomy? What factors drive generalization? What are the model/data scaling curves like? Real-world eval is slow and noisy, and existing sims (like LIBERO, which we built 3 years ago) often lack sufficient task and scene diversity. This benchmark comes with 2,200+ hours of demonstrations and 500K+ trajectories to support studies of multi-task training, pretraining, and continual learning at scale. Check it out at

Today, we publicly released RoboCasa365, a large-scale simulation benchmark for training and systematically evaluating generalist robot models. Built upon our original RoboCasa framework, it offers: • 2,500 realistic kitchen environments; • 365 everyday tasks (basic skills + long-horizon mobile manipulation); • Over 3,200 objects with many articulated fixtures/appliances. All are designed for fully controlled, reproducible benchmarking of robotic policies. Progress in robotic foundation models is real. But it’s still hard to answer basic questions like: How close are we to general-purpose autonomy? What factors drive generalization? What are the model/data scaling curves like? Real-world eval is slow and noisy, and existing sims (like LIBERO, which we built 3 years ago) often lack sufficient task and scene diversity. This benchmark comes with 2,200+ hours of demonstrations and 500K+ trajectories to support studies of multi-task training, pretraining, and continual learning at scale. Check it out at

Yuke Zhu

24,027 次观看 • 6 个月前

Apple's AI Reasoning Model Paper Explained Apple’s disruptive new AI reasoning model research paper, “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models” explained, and what it means for AGI.

Apple's AI Reasoning Model Paper Explained Apple’s disruptive new AI reasoning model research paper, “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models” explained, and what it means for AGI.

Harper Carroll

37,956 次观看 • 1 年前

Introducing GLM-5.1 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing GLM-5.1 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

31,027 次观看 • 5 个月前

Introducing o3-mini for understanding arXiv papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing o3-mini for understanding arXiv papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

66,598 次观看 • 1 年前

Introducing GPT OSS for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing GPT OSS for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

29,515 次观看 • 1 年前

VLAs offer an avenue for generalist robot policies; however, naively following the action predictions leads to brittle or unsafe behaviours. We introduce VLAPS, which integrates model-based search with pre-trained VLA policies to improve performance without additional training.

VLAs offer an avenue for generalist robot policies; however, naively following the action predictions leads to brittle or unsafe behaviours. We introduce VLAPS, which integrates model-based search with pre-trained VLA policies to improve performance without additional training.

Glen Berseth

13,374 次观看 • 1 年前

Introducing Grok 4 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing Grok 4 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

88,392 次观看 • 1 年前

Scalable, reproducible, and reliable robotic evaluation remains an open challenge, especially in the age of generalist robot foundation models. Can *simulation* effectively predict *real-world* robot policy performance & behavior? Presenting SIMPLER!👇

Scalable, reproducible, and reliable robotic evaluation remains an open challenge, especially in the age of generalist robot foundation models. Can simulation effectively predict real-world robot policy performance & behavior? Presenting SIMPLER!👇

Xuanlin Li (Simon)

86,460 次观看 • 2 年前

Introducing Gemini 3 Flash for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing Gemini 3 Flash for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

48,596 次观看 • 8 个月前

Introducing Qwen 3 Reasoning for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing Qwen 3 Reasoning for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

24,011 次观看 • 1 年前

Introducing Gemini 3 Pro for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing Gemini 3 Pro for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

50,035 次观看 • 9 个月前

Introducing GLM 5 Turbo for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing GLM 5 Turbo for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

23,384 次观看 • 5 个月前

Introducing Claude Sonnet 4.6 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

Introducing Claude Sonnet 4.6 for understanding research papers 🚀 Highlight any section of a paper to ask questions and “@” other papers for quick context, comparisons, and benchmark references

alphaXiv

49,186 次观看 • 6 个月前