Researchers have created a new resource that enables artificial intelligence to translate natural language descriptions into accurate and detailed scientific architecture diagrams.
A new framework leverages agentic systems and deterministic graph traversal to unlock deeper insights from complex enterprise document collections.
As generative AI tools proliferate, a growing number of queer artists are critically examining – and often rejecting – their use, prioritizing ethical data practices and the preservation of artistic community.
![The system navigates treacherous, mixed terrain-slushy snow over grass-by resolving the visual-texture paradox inherent in relying solely on vision, instead integrating proprioceptive data to estimate contextual understanding and facilitate robust locomotion, as demonstrated by the differentiation from vision-only approaches detailed in [12] and segmentation methods outlined in [40].](https://arxiv.org/html/2604.14344v1/x1.png)
A new control framework integrates visual and sensor data to allow legged robots to navigate challenging landscapes with improved stability and efficiency.
New research details a framework for automatically uncovering the causal links between the behaviors of AI agents and the complex results they produce.
A new framework integrates robotic sorting with optimized anaerobic digestion to dramatically improve the efficiency and sustainability of waste management.
Researchers have developed a generative agent that simulates how a student’s understanding grows over time, offering a more nuanced and realistic approach to personalized learning.
New technologies are transforming forestry, enabling more precise management and sustainable harvesting practices.
A new framework proposes that understanding the local interactions of AI agents is key to preventing unpredictable and potentially harmful outcomes in complex systems.
A new approach leverages shared visual understanding to refine image annotation, bridging the gap between human perception and machine learning.