Tesla’s Full Self-Driving system relies on autoregressive transformers to predict and navigate complex driving scenarios. This technology represents a major leap in autonomous vehicle AI.

Over the last decade, artificial intelligence (AI) has been largely built around large language models (LLMs). These systems are based on a language and guess words in a chain in the form of tokens.

While GlobalData analyst Sara Reci touted the DRAGON results as a “breakthrough” in STGD1, she noted that barriers to ...

Tinlarebant is the first therapeutic candidate to demonstrate clinical efficacy in a global Phase 3 trial for Stargardt ...

The authors find that digital services trade and sectoral development play a significantly stronger role in boosting IP ...

ABSTRACT: In this study, we employ a spatial unsupervised classification technique to analyze the spatio-temporal variability of Sea Surface Temperature (SST) in the tropical African zone. The ...

🤔 Can autoregressive visual generation supervision improve VLMs' understanding capability? 🚀 Reconstructing the visual semantics of images leads to better visual comprehension. Abstract. Typical ...

Jun 5, 2025: The initial code for training and inference is released. See GETTING_STARTED.md and give it a try now! Most cases have been tested but if you find bugs, feel free to open an issue.

Abstract: Designing a universal policy architecture that performs well across diverse robots and task configurations remains a key challenge. In this work, we address this by representing robot ...

Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at handling large datasets and are very strong at ...

Generative models based on diffusion processes have shown great promise in transforming noise into data, but they face key challenges in flexibility and efficiency. Existing diffusion models typically ...