Rephonic
Artwork for RoboPapers
Reinforcement Learning
Robotics
Vision-Language Models
Project Instinct
Humanoid Robots
Sim-To-Real
R2S2
Dreamzero
Molmospaces
Imitation Learning
Unifp
Sim2real
Humanoid Everyday
Force Sensing
Maniflow
Diffusion Policy
Attention-Based Map Encoding For Learning Generalized Legged Locomotion
General Intuition
Whole Body Conditioned, Egocentric Video Prediction
Domain Randomization

Chris Paxton & Michael Cho geek out over robotic papers with paper authors. robopapers.substack.com

PublishesTwice weeklyEpisodes81Founded6 months ago
Number of ListenersCategories
TechnologyScience

Listen to this Podcast

Artwork for RoboPapers

Latest Episodes

Robotics fundamentally involves understanding the dynamics of how things change in the world in response to action and force. This is impossible to learn from static images; instead, it’s far more effective and more data-efficient to learn from video... more

Sports like tennis are great examples of the sort of dynamic whole-body interaction that’s possible with humanoid robots. But capturing examples of fast, dynamic interactions from humans is really difficult. Enter LATENT, which uses lower-quality hum... more

Training robot foundation models faces two key hurdles: how to get enough data to train an effective model, and how to make sure that new skills can be acquired quickly. The team at Rhoda AI believes that the answer is training Direct Video Action mo... more

Robotics has changed dramatically over the last eight years. Ted has been involved in the cutting edge of robot learning through this period, spending those eight years at Google Brain/Google Deepmind. And he’s identified three eras of robot learning... more

Key Facts

Accepts Guests
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

Recent Guests

Jose Barreiros
Senior Scientist / Tech Lead at TRI (Utah Research Institute)
TRI (Utah Research Institute)
Episode: Ep#70: A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation
Fanqi Lin
PhD student at Tsinghua University; intern at TRI
Tsinghua University; TRI
Episode: Ep#70: A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation
Yejin Kim
Research engineer leading MolmoSpaces project
Allard Institute for AI
Episode: Ep#69: MolmoSpaces, an Open Ecosystem for Embodied AI
Omar Rayyan
First-year PhD student working on MolmoSpaces
UCLA / AI2
Episode: Ep#69: MolmoSpaces, an Open Ecosystem for Embodied AI
Max Argus
Postdoctoral researcher focused on computer vision for robots
AI2
Episode: Ep#69: MolmoSpaces, an Open Ecosystem for Embodied AI
Seonghyeon Ye
Co-author of DreamZero, PhD student at KAIS, research intern at NVIDIA
KAIS, NVIDIA
Episode: Ep#68: DreamZero: World Action Models are Zero-Shot Policies
Jianke Zhang
First author of VLM4Vla, PhD student at Tsinghua University
Tsinghua University
Episode: Ep#65: VLM4VLA: Revisiting Vision-Language Models in Vision-Language-Action Models
Shaoting Zhu
PhD student and researcher on Project Instinct
Project Instinct / Instinct Lab
Episode: Ep#64: Project Instinct
Hongyu Li
Co-author, Brown PhD student, co-author on NovaFlow
Brown University/RAI Robotics and AI Institute
Episode: Ep#63: NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos

Hosts

Chris Paxton
Host of RoboPapers (co-host)
Michael Cho
Host of RoboPapers (co-host)
Jiafei
Host/Questioner; appears as guest-host in some episodes

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#240
United Kingdom/Technology
Apple Podcasts
#34
Mexico/Technology
Apple Podcasts
#198
Netherlands/Technology

Talking Points

Recent interactions between the hosts and their guests.

Ep#33: A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search
Q: What are the main bottlenecks to reaching 100% success across tasks?
Limitations come from world model fidelity, reward model accuracy, and the planner's compute budget; improving any of these components through better representations, more data, or more efficient planning can push performance closer to perfect.
Ep#33: A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search
Q: Does Sailor really require much data, or can world models and reward models compensate for less demonstrations?
Yes, Sailor can achieve strong performance with relatively few demonstrations because the reward model differentiates good versus bad states and test-time planning refines base actions, reducing reliance on massive expert datasets.
Ep#40: Daxo Robotics
Q: How scalable is the technology, and can it be integrated with existing robotic arms?
The design is intended to be modular and scalable, with next versions aiming to reduce volume by 98% and enable integration with existing robotic arms while maintaining payload, meaning the hand could become a drop-in component for different platforms.
Ep#40: Daxo Robotics
Q: Why did you pivot from agricultural robots to a hand with soft robot mechanisms?
The pivot came from recognizing a compelling, universal need for dexterous manipulation. The soft, tendon-driven approach promised infinite degrees of freedom and high redundancy, enabling more adaptable and safer interaction with real-world objects like fruits and papers, which inspired a broader vision for versatile manipulation.
Ep#28: DreamGen: Unlocking Generalization in Robot Learning through Video World Models
Q: How many teleoperation data points are needed to achieve adaptability?
Approximately 100 teleoperation samples are enough to enable the ontology of adaptability, with substantial gains when augmented by neural trajectories and co-training.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

Listeners per Episode
Gender Skew
Location
Interests
Professions
Age Range
Household Income
Social Media Reach

Frequently Asked Questions About RoboPapers

What is RoboPapers about and what kind of topics does it cover?

Technical deep dives into robotics research papers, simulation benchmarks, and open hardware/software projects. Across recent episodes, the show spotlights embodied AI, world models, sim-to-real transfer, and hands-on robotics systems, with guests ranging from university researchers to industrial labs. Discussions emphasize practical engineering challenges, data strategies, and open ecosystems, often exploring how new papers translate into runnable pipelines, benchmarks, and hardware implementations. The format tends to blend theory with hands-on demonstrations, and notable recurring themes include scalable simulation platforms, zero-shot or few-shot policy transfer, and community-driven benchmarking. This mix is likely to appeal to enginee... more

Where can I find podcast stats for RoboPapers?

Rephonic provides a wide range of podcast stats for RoboPapers. We scanned the web and collated all of the information that we could find in our comprehensive podcast database. See how many people listen to RoboPapers and access YouTube viewership numbers, download stats, audience demographics, chart rankings, ratings, reviews and more.

How many listeners does RoboPapers get?

Rephonic provides a full set of podcast information for three million podcasts, including the number of listeners. View further listenership figures for RoboPapers, including podcast download numbers and subscriber numbers, so you can make better decisions about which podcasts to sponsor or be a guest on. You will need to upgrade your account to access this premium data.

What are the audience demographics for RoboPapers?

Rephonic provides comprehensive predictive audience data for RoboPapers, including gender skew, age, country, political leaning, income, professions, education level, and interests. You can access these listener demographics by upgrading your account.

How many subscribers and views does RoboPapers have?

To see how many followers or subscribers RoboPapers has on Spotify and other platforms such as Castbox and Podcast Addict, simply upgrade your account. You'll also find viewership figures for their YouTube channel if they have one.

How many episodes of RoboPapers are there?

RoboPapers launched 6 months ago and published 81 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

How do I contact RoboPapers?

Our systems regularly scour the web to find email addresses and social media links for this podcast. We scanned the web and collated all of the contact information that we could find in our podcast database. But in the unlikely event that you can't find what you're looking for, our concierge service lets you request our research team to source better contacts for you.

Where can I see ratings and reviews for RoboPapers?

Rephonic pulls ratings and reviews for RoboPapers from multiple sources, including Spotify, Apple Podcasts, Castbox, and Podcast Addict.

View all the reviews in one place instead of visiting each platform individually and use this information to decide if a show is worth pitching or not.

How do I access podcast episode transcripts for RoboPapers?

Rephonic provides full transcripts for episodes of RoboPapers. Search within each transcript for your keywords, whether they be topics, brands or people, and figure out if it's worth pitching as a guest or sponsor. You can even set-up alerts to get notified when your keywords are mentioned.

What guests have appeared on RoboPapers?

Recent guests on RoboPapers include:

1. Jose Barreiros
2. Fanqi Lin
3. Yejin Kim
4. Omar Rayyan
5. Max Argus
6. Seonghyeon Ye
7. Jianke Zhang
8. Shaoting Zhu

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

Find and pitch the right podcasts

We help savvy brands, marketers and PR professionals to find the right podcasts for any topic or niche. Get the data and contacts you need to pitch podcasts at scale and turn listeners into customers.
Try it free for 7 days