Scientific discovery in the age of artificial intelligence
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …
and accelerate research, hel** scientists to generate hypotheses, design experiments …
Challenges and applications of large language models
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
Harnessing the power of llms in practice: A survey on chatgpt and beyond
This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …
working with Large Language Models (LLMs) in their downstream Natural Language …
Faith and fate: Limits of transformers on compositionality
Transformer large language models (LLMs) have sparked admiration for their exceptional
performance on tasks that demand intricate multi-step reasoning. Yet, these models …
performance on tasks that demand intricate multi-step reasoning. Yet, these models …
End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
Cambrian-1: A fully open, vision-centric exploration of multimodal llms
We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-
centric approach. While stronger language models can enhance multimodal capabilities, the …
centric approach. While stronger language models can enhance multimodal capabilities, the …
Robust speech recognition via large-scale weak supervision
We study the capabilities of speech processing systems trained simply to predict large
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
Foundations & trends in multimodal machine learning: Principles, challenges, and open questions
Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
When and why vision-language models behave like bags-of-words, and what to do about it?
Despite the success of large vision and language models (VLMs) in many downstream
applications, it is unclear how well they encode compositional information. Here, we create …
applications, it is unclear how well they encode compositional information. Here, we create …
Self-supervised learning in medicine and healthcare
The development of medical applications of machine learning has required manual
annotation of data, often by medical experts. Yet, the availability of large-scale unannotated …
annotation of data, often by medical experts. Yet, the availability of large-scale unannotated …