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 streamlines the modeling and planning of intricate manipulation tasks for soft robots operating in contact-rich scenarios.
A new framework uses artificial intelligence to autonomously discover single-atom catalysts with performance exceeding established chemical principles.
![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.
Researchers have developed a novel motion planning system that allows robots to navigate complex home environments with increased speed, safety, and reliability.