Orr Krupnik
@orrkrup.bsky.social
ML Research @ Tzafon | Prev: Robot Learning & RL PhD @Technion
More data isn't all we need 🔭🦾 🌍
More data isn't all we need 🔭🦾 🌍
Are there any good robotics and/or RL podcasts still running in 2025?
I used to enjoy The Robot Brains by Pieter Abbeel and TalkRL by @robinchauhan.bsky.social , but open to different styles too!
I used to enjoy The Robot Brains by Pieter Abbeel and TalkRL by @robinchauhan.bsky.social , but open to different styles too!
July 18, 2025 at 7:02 AM
Are there any good robotics and/or RL podcasts still running in 2025?
I used to enjoy The Robot Brains by Pieter Abbeel and TalkRL by @robinchauhan.bsky.social , but open to different styles too!
I used to enjoy The Robot Brains by Pieter Abbeel and TalkRL by @robinchauhan.bsky.social , but open to different styles too!
I find this idea really neat - VLMs are great at describing scenes, but LLMs are better reasoners, so let's use text as an interim representation.
Kind of reminiscent of the bitter lesson, only on a more "local" scale
arxiv.org/abs/2503.15108
Kind of reminiscent of the bitter lesson, only on a more "local" scale
arxiv.org/abs/2503.15108
VIPER: Visual Perception and Explainable Reasoning for Sequential Decision-Making
While Large Language Models (LLMs) excel at reasoning on text and Vision-Language Models (VLMs) are highly effective for visual perception, applying those models for visual instruction-based planning ...
arxiv.org
April 22, 2025 at 11:00 AM
I find this idea really neat - VLMs are great at describing scenes, but LLMs are better reasoners, so let's use text as an interim representation.
Kind of reminiscent of the bitter lesson, only on a more "local" scale
arxiv.org/abs/2503.15108
Kind of reminiscent of the bitter lesson, only on a more "local" scale
arxiv.org/abs/2503.15108
Reposted by Orr Krupnik
Check out our new #ICLR2025 paper: EC-Diffuser leverages a novel Transformer-based diffusion denoiser to learn goal-conditioned multi-object manipulation policy from pixels!👇
Paper: www.arxiv.org/abs/2412.18907
Project page: sites.google.com/view/ec-diff...
Code: github.com/carl-qi/EC-D...
Paper: www.arxiv.org/abs/2412.18907
Project page: sites.google.com/view/ec-diff...
Code: github.com/carl-qi/EC-D...
February 19, 2025 at 4:10 PM
Check out our new #ICLR2025 paper: EC-Diffuser leverages a novel Transformer-based diffusion denoiser to learn goal-conditioned multi-object manipulation policy from pixels!👇
Paper: www.arxiv.org/abs/2412.18907
Project page: sites.google.com/view/ec-diff...
Code: github.com/carl-qi/EC-D...
Paper: www.arxiv.org/abs/2412.18907
Project page: sites.google.com/view/ec-diff...
Code: github.com/carl-qi/EC-D...
Reposted by Orr Krupnik
If interested on our take on addressing inverse RL in large state spaces, go to meet @filippo_lazzati and @alberto_metelli in the poster session 5 #NeurIPS2024 today (paper -> arxiv.org/abs/2406.03812)
December 13, 2024 at 2:33 PM
If interested on our take on addressing inverse RL in large state spaces, go to meet @filippo_lazzati and @alberto_metelli in the poster session 5 #NeurIPS2024 today (paper -> arxiv.org/abs/2406.03812)
Reposted by Orr Krupnik
Want to learn / teach RL?
Check out new book draft:
Reinforcement Learning - Foundations sites.google.com/view/rlfound...
W/ Shie Mannor & Yishay Mansour
This is a rigorous first course in RL, based on our teaching at TAU CS and Technion ECE.
Check out new book draft:
Reinforcement Learning - Foundations sites.google.com/view/rlfound...
W/ Shie Mannor & Yishay Mansour
This is a rigorous first course in RL, based on our teaching at TAU CS and Technion ECE.
November 25, 2024 at 12:08 PM
Want to learn / teach RL?
Check out new book draft:
Reinforcement Learning - Foundations sites.google.com/view/rlfound...
W/ Shie Mannor & Yishay Mansour
This is a rigorous first course in RL, based on our teaching at TAU CS and Technion ECE.
Check out new book draft:
Reinforcement Learning - Foundations sites.google.com/view/rlfound...
W/ Shie Mannor & Yishay Mansour
This is a rigorous first course in RL, based on our teaching at TAU CS and Technion ECE.
Some papers really feel like a glimpse into the future!
This one also serves as a powerful reminder that a lot of what we're focused on in the AI + robotics space is constrained by the hardware we have.
arxiv.org/abs/2411.11192
This one also serves as a powerful reminder that a lot of what we're focused on in the AI + robotics space is constrained by the hardware we have.
arxiv.org/abs/2411.11192
Robot Metabolism: Towards machines that can grow by consuming other machines
Biological lifeforms can heal, grow, adapt, and reproduce -- abilities essential for sustained survival and development. In contrast, robots today are primarily monolithic machines with limited abilit...
arxiv.org
November 19, 2024 at 6:53 PM
Some papers really feel like a glimpse into the future!
This one also serves as a powerful reminder that a lot of what we're focused on in the AI + robotics space is constrained by the hardware we have.
arxiv.org/abs/2411.11192
This one also serves as a powerful reminder that a lot of what we're focused on in the AI + robotics space is constrained by the hardware we have.
arxiv.org/abs/2411.11192