A review of large language models and autonomous agents in chemistry
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …
impacting molecule design, property prediction, and synthesis optimization. This review …
Deep learning in sentiment analysis: Recent architectures
T Abdullah, A Ahmet - ACM Computing Surveys, 2022 - dl.acm.org
Humans are increasingly integrated with devices that enable the collection of vast
unstructured opinionated data. Accurately analysing subjective information from this data is …
unstructured opinionated data. Accurately analysing subjective information from this data is …
Is ChatGPT a general-purpose natural language processing task solver?
Spurred by advancements in scale, large language models (LLMs) have demonstrated the
ability to perform a variety of natural language processing (NLP) tasks zero-shot--ie, without …
ability to perform a variety of natural language processing (NLP) tasks zero-shot--ie, without …
Latent diffusion for language generation
Diffusion models have achieved great success in modeling continuous data modalities such
as images, audio, and video, but have seen limited use in discrete domains such as …
as images, audio, and video, but have seen limited use in discrete domains such as …
Nougat: Neural optical understanding for academic documents
Scientific knowledge is predominantly stored in books and scientific journals, often in the
form of PDFs. However, the PDF format leads to a loss of semantic information, particularly …
form of PDFs. However, the PDF format leads to a loss of semantic information, particularly …
Menstrual irregularities and vaginal bleeding after COVID-19 vaccination reported to v-safe active surveillance, USA in December, 2020–January, 2022: an …
KK Wong, CM Heilig, A Hause, TR Myers… - The Lancet Digital …, 2022 - thelancet.com
Background Anecdotal reports of menstrual irregularities after receiving COVID-19 vaccines
have been observed in post-authorisation and post-licensure monitoring. We aimed to …
have been observed in post-authorisation and post-licensure monitoring. We aimed to …
Ares: An automated evaluation framework for retrieval-augmented generation systems
Evaluating retrieval-augmented generation (RAG) systems traditionally relies on hand
annotations for input queries, passages to retrieve, and responses to generate. We …
annotations for input queries, passages to retrieve, and responses to generate. We …
Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning
M Ashayeri, N Abbasabadi - Energy and Buildings, 2024 - Elsevier
This study explores the intricate relationship between human sentiment on social media
data, herein tweet posts on X platform, urban building characteristics, and the socio-spatial …
data, herein tweet posts on X platform, urban building characteristics, and the socio-spatial …
The implementation of the cognitive theory of multimedia learning in the design and evaluation of an AI educational video assistant utilizing large language models
Abstract The integration of Artificial Intelligence (AI) holds immense potential for
revolutionizing education; especially, in contexts where multimodal learning experiences …
revolutionizing education; especially, in contexts where multimodal learning experiences …
Self-supervised pretraining and transfer learning enable\titlebreak flu and covid-19 predictions in small mobile sensing datasets
MA Merrill, T Althoff - Conference on Health, Inference, and …, 2023 - proceedings.mlr.press
Detailed mobile sensing data from phones and fitness trackers offer an opportunity to
quantify previously unmeasurable behavioral changes to improve individual health and …
quantify previously unmeasurable behavioral changes to improve individual health and …