Researchers have developed a new representation learning framework that allows robots to better understand and interact with objects, leading to more reliable and adaptable manipulation skills.
This review explores how quantitative modeling of fluorescence experiments is advancing our ability to predict dye behavior and unlock new insights into biomolecular structure and dynamics.
New research introduces a benchmark to measure how effectively humans and artificial intelligence establish shared understanding during collaborative tasks.
A new framework reveals how an individual’s existing beliefs can undermine even the most accurate AI-powered decision support systems.
A new framework uses artificial intelligence to autonomously discover single-atom catalysts with performance exceeding established chemical principles.
A new framework streamlines the modeling and planning of intricate manipulation tasks for soft robots operating in contact-rich scenarios.
![SymTorch facilitates symbolic distillation by wrapping neural network components, collecting input-output data during forward passes, and employing PySR to generate increasingly complex symbolic regressions-allowing for the replacement of these components with optimized equations and the creation of hybrid neural-symbolic models that balance expressiveness and computational efficiency, effectively distilling the function of a neural network into a mathematically provable form [latex] f(x) = \sum_{i=0}^{n} a_i x^i [/latex].](https://arxiv.org/html/2602.21307v1/images/figure1.png)
Researchers have developed a framework to automatically extract symbolic expressions from deep learning models, bridging the gap between black-box prediction and human-understandable reasoning.
New research details a framework for building more natural human-robot interactions by enabling robots to shift their gaze in a way that mimics human behavior.
A new approach leverages field theory and partial differential equations to create more robust and context-aware memory systems for AI agents.
Researchers have developed an autonomous underwater vehicle modeled after sea turtles, enabling agile navigation and tracking in challenging marine environments.