Robots Learn to Grasp in a Single Step
Researchers have developed a new visuomotor policy that moves crucial refinement steps from runtime to training, enabling robots to perform complex grasps with unprecedented speed and accuracy.
Science
Uncovering Hidden Structure for Better AI Representations
New research demonstrates a method for automatically learning underlying symmetries in data to create more interpretable and effective artificial intelligence models.
Unlocking Ancient Ecosystems with AI-Powered Phytolith Analysis
A new platform harnesses the power of artificial intelligence to automate the study of microscopic plant remains, offering unprecedented insights into past environments and human-plant interactions.
Robotic Hands Hit the Right Notes: Teaching Robots to Play Piano
![HandelBot consistently outperformed alternative methods in achieving precise piano performance, evidenced by its superior F1 score, and highlighting the critical role of real-world samples in bridging the performance gap inherent in systems relying solely on simulated data-a gap that significantly hindered the effectiveness of methods like [latex]\pi_{sim}(CL)[/latex] and [latex]\pi_{sim}[/latex].](https://arxiv.org/html/2603.12243v1/x3.png)
Researchers have developed a new framework that enables robots to learn complex piano playing skills in the real world through a combination of simulation and adaptive learning.
The AI Echo Chamber: How Pathology Decisions Get Stuck on Suggestions
New research reveals that artificial intelligence assistance in pathology isn’t neutral, leading to predictable biases that can impact diagnostic accuracy.
Bridging the Gap: Human Motion for Robots
Researchers have developed a new pipeline for seamlessly transferring natural human movements to humanoid robots, enabling more fluid and realistic robotic interactions.
AI’s Subtle Script: How Recruitment Tools Perpetuate Gender Stereotypes
New research reveals that while AI-powered recruitment tools don’t inherently favor one gender over another in job suggestions, they subtly reinforce traditional stereotypes through the language used to describe candidates.
Beyond Randomness: Measuring Diversity for Smarter Robots
A new metric, leveraging kernel methods, offers a fast and model-free way to quantify and improve the diversity of datasets used in robotic imitation learning.
Can AI Learn to Play Fair? Replicating Human Norms in Multi-Agent Systems
A new framework allows researchers to rigorously test how AI agents understand and apply principles of fairness by directly translating human subject experiments for artificial intelligence.
Robots That Teach Themselves: Closing the Loop on Data Collection
A new system combines semantic planning and autonomous environment resets to enable robots to continuously gather training data without human intervention.