Researchers have developed a novel method that empowers image generators to ‘think’ through their creations, iteratively refining both prompts and visuals for dramatically improved results.
Researchers have developed a new framework that brings more realistic human behavior to social media simulations by incorporating personality traits and emotional responses.
Researchers have developed a novel approach to soft robotics, creating an inflatable robot with a wide range of motion thanks to innovative pneumatic bladder links and Hilberry joints.
Researchers are leveraging the power of generative artificial intelligence to automatically create realistic database workloads, accelerating the development and optimization of key database components.
Researchers have developed a system that uses artificial intelligence to translate descriptive scenes into dynamic actions for virtual agents, enabling procedurally generated interactive narratives.
A new framework combines the power of large language models with a multi-agent system to significantly improve the accuracy and flexibility of predicting outcomes in ongoing processes.
A new benchmark reveals that while large language models excel at following instructions, they struggle with the spatial awareness and social reasoning needed to navigate real-world interactions.
A new framework aims to shed light on how artificial intelligence models arrive at solutions for coding tasks, offering developers deeper insights into their behavior.
Researchers unveil TongSIM, a comprehensive environment for training and testing intelligent agents in realistic, multimodal scenarios.
A new benchmark reveals that vision-language models struggle with basic physical reasoning, often relying on memorization rather than genuine understanding of visual scenes.