Researchers have developed a new system that blends human creativity with artificial intelligence to streamline the design of visually engaging and narratively consistent infographics.
Researchers have developed an agent that achieves provable optimality in reinforcement learning without relying on pre-defined models of its environment.
A new study leverages a unique dataset to reveal the systematic ways people approach abstract reasoning, offering crucial insights for building more human-aligned artificial intelligence.
Researchers are harnessing the power of author networks and advanced AI techniques to generate truly novel and feasible scientific ideas.
![A novel framework leverages a transformer-based gloss-free sign language model to directly translate continuous sign videos into natural language instructions, employing an encoder to distill spatiotemporal features and a decoder to generate grounded commands for a virtual agent policy [32].](https://arxiv.org/html/2602.22514v1/2602.22514v1/meida/Signformer.jpg)
Researchers have developed a new framework that allows robots to understand and respond to sign language gestures in real-time, opening doors to more intuitive and accessible human-robot collaboration.
A new open-source framework, MiroFlow, aims to improve the reliability and performance of AI agents tackling complex research challenges.
As AutoML systems grow more complex, understanding how they reach decisions is as crucial as the resulting model performance.
A new framework leverages principles of predictive processing to improve how robots anticipate and react to obscured pedestrians in complex urban environments.
A new framework, InCoM, dynamically focuses perception and coordinates full-body movement to achieve more robust and adaptable mobile manipulation.
A new agentic platform leverages the power of large language models to help researchers discover trustworthy references and streamline the writing process.