Seeing Through the Clutter: AI Helps Robots Grasp Objects with Confidence

New research demonstrates a powerful AI system that allows robots to reliably identify and grasp objects even in complex, cluttered scenes.

New research demonstrates a powerful AI system that allows robots to reliably identify and grasp objects even in complex, cluttered scenes.

A new approach integrates Lie group theory with convolutional neural networks to capture the inherent symmetries within language and improve sentence classification accuracy.

New research reveals how to overcome limitations in collaborative AI systems where agents have differing levels of information access.

A new reinforcement learning framework empowers large language models to dynamically decide when to consult external knowledge, improving both performance and self-awareness.
A new framework leverages the power of multiple large language models to automate the complex process of qualitative data analysis.
![As noise increases in experimental data, learned dimensionless group coefficients demonstrably drift from their true values-specifically, away from the expected $ [1,1,0]^{T}$-highlighting a fundamental challenge in identifying these groups from noisy observations, even with uncertainty captured across twenty ensemble runs.](https://arxiv.org/html/2512.15760v1/Figures/noise_effect_gamma.png)
This review explores how combining physics-inspired scaling analysis with machine learning can reveal fundamental relationships within complex datasets.

Researchers have developed a new framework that accurately forecasts 3D hand movements by combining visual understanding with linguistic context from human interaction videos.

A new framework combines the power of graph networks and language models to accurately forecast the performance of complex, AI-driven workflows.
A vintage typewriter, reborn with the power of a large language model, offers a unique lens for examining our relationship with technology, nostalgia, and the pace of information.

Researchers have developed a novel framework for analyzing complex, evolving data by representing it as geometric patterns within vector fields.