On the path to achieving artificial superhuman intelligence, a critical tipping point lies in a system’s ability to drive its own improvement independently, without relying on human-provided data, ...

While large language models (LLMs) dominate the AI landscape, Small-scale Large Language Models (SLMs) are gaining traction as cost-effective and efficient alternatives for various applications.

The field of text-to-image synthesis has advanced rapidly, with state-of-the-art models now generating highly realistic and diverse images from text descriptions. This progress largely owes to ...

Consistency models (CMs) are a cutting-edge class of diffusion-based generative models designed for rapid and efficient sampling. However, most existing CMs rely on discretized timesteps, which ...

Large Language Models (LLMs) have advanced considerably in generating and understanding text, and recent developments have extended these capabilities to multimodal LLMs that integrate both visual and ...

OpenAI researchers introduces TrigFlow, a simplified theoretical framework that identifies the key causes of training instability of consistency models and addresses them with novel improvements in ...

In cognitive science, human thought processes are commonly divided into two systems: the fast, intuitive System 1 and the slower, analytical System 2. Recent research has shown that incorporating ...

Generative AI, including Language Models (LMs), holds the promise to reshape key sectors like education, healthcare, and law, which rely heavily on skilled professionals to navigate complex ...