Astronomia ex machina: a history, primer and outlook on neural networks in astronomy
In this review, we explore the historical development and future prospects of artificial
intelligence (AI) and deep learning in astronomy. We trace the evolution of connectionism in …
intelligence (AI) and deep learning in astronomy. We trace the evolution of connectionism in …
Embers of autoregression: Understanding large language models through the problem they are trained to solve
The widespread adoption of large language models (LLMs) makes it important to recognize
their strengths and limitations. We argue that in order to develop a holistic understanding of …
their strengths and limitations. We argue that in order to develop a holistic understanding of …
Driving and suppressing the human language network using large language models
Transformer models such as GPT generate human-like language and are predictive of
human brain responses to language. Here, using functional-MRI-measured brain responses …
human brain responses to language. Here, using functional-MRI-measured brain responses …
Generative representational instruction tuning
All text-based language problems can be reduced to either generation or embedding.
Current models only perform well at one or the other. We introduce generative …
Current models only perform well at one or the other. We introduce generative …
Can neural networks do arithmetic? a survey on the elementary numerical skills of state-of-the-art deep learning models
A Testolin - Applied Sciences, 2024 - mdpi.com
Creating learning models that can exhibit sophisticated reasoning abilities is one of the
greatest challenges in deep learning research, and mathematics is rapidly becoming one of …
greatest challenges in deep learning research, and mathematics is rapidly becoming one of …
Scaling law for recommendation models: Towards general-purpose user representations
Recent advancement of large-scale pretrained models such as BERT, GPT-3, CLIP, and
Gopher, has shown astonishing achievements across various task domains. Unlike vision …
Gopher, has shown astonishing achievements across various task domains. Unlike vision …
Instructprotein: Aligning human and protein language via knowledge instruction
Large Language Models (LLMs) have revolutionized the field of natural language
processing, but they fall short in comprehending biological sequences such as proteins. To …
processing, but they fall short in comprehending biological sequences such as proteins. To …
Infusing behavior science into large language models for activity coaching
Large language models (LLMs) have shown promise for task-oriented dialogue across a
range of domains. The use of LLMs in health and fitness coaching is under-explored …
range of domains. The use of LLMs in health and fitness coaching is under-explored …
A survey on text classification: Practical perspectives on the Italian language
Text Classification methods have been improving at an unparalleled speed in the last
decade thanks to the success brought about by deep learning. Historically, state-of-the-art …
decade thanks to the success brought about by deep learning. Historically, state-of-the-art …
Clueweb22: 10 billion web documents with visual and semantic information
A Overwijk, C Xiong, X Liu, C VandenBerg… - arXiv preprint arXiv …, 2022 - arxiv.org
ClueWeb22, the newest iteration of the ClueWeb line of datasets, provides 10 billion web
pages affiliated with rich information. Its design was influenced by the need for a high …
pages affiliated with rich information. Its design was influenced by the need for a high …