The recent Nobel Prize for groundbreaking advancements in protein discovery underscores the transformative potential of foundation models (FMs) in exploring vast combinatorial spaces. These models are ...

The transformative impact of Transformers on natural language processing (NLP) and computer vision (CV) is undeniable. Their scalability and effectiveness have propelled advancements across these ...

Large Language Models (LLMs) have become indispensable tools for diverse natural language processing (NLP) tasks. Traditional LLMs operate at the token level, generating output one word or subword at ...

The Transformer architecture, introduced by Vaswani et al. in 2017, serves as the backbone of contemporary language models. Over the years, numerous modifications to this architecture have been ...

Recent advancements in training large multimodal models have been driven by efforts to eliminate modeling constraints and unify architectures across domains. Despite these strides, many existing ...

A research team presents GPUDrive, a GPU-accelerated multi-agent simulator built on the Madrona Game Engine, which is capable of generating over a million experience steps per second, making it a game ...

Navigation is a fundamental skill for any visually-capable organism, serving as a critical tool for survival. It enables agents to locate resources, find shelter, and avoid threats. In humans, ...

Language models (LMs) based on transformers have become the gold standard in natural language processing, thanks to their exceptional performance, parallel processing capabilities, and ability 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 ...

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.