A survey on event extraction for natural language understanding: Riding the biomedical literature wave
Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …
Bioreader: a retrieval-enhanced text-to-text transformer for biomedical literature
The latest batch of research has equipped language models with the ability to attend over
relevant and factual information from non-parametric external sources, drawing a …
relevant and factual information from non-parametric external sources, drawing a …
Semantic self-segmentation for abstractive summarization of long documents in low-resource regimes
The quadratic memory complexity of transformers prevents long document summarization in
low computational resource scenarios. State-of-the-art models need to apply input …
low computational resource scenarios. State-of-the-art models need to apply input …
Efficient memory-enhanced transformer for long-document summarization in low-resource regimes
Long document summarization poses obstacles to current generative transformer-based
models because of the broad context to process and understand. Indeed, detecting long …
models because of the broad context to process and understand. Indeed, detecting long …
Carburacy: summarization models tuning and comparison in eco-sustainable regimes with a novel carbon-aware accuracy
Generative transformer-based models have reached cutting-edge performance in long
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
Recent trends and advances in deep learning-based sentiment analysis
A Ahmet, T Abdullah - Deep learning-based approaches for sentiment …, 2020 - Springer
Sentiment analysis is a fundamental branch of natural language processing. It is an
essential task of identifying and extracting sentiment in opinionated data from sources such …
essential task of identifying and extracting sentiment in opinionated data from sources such …
Lawsuit: a large expert-written summarization dataset of italian constitutional court verdicts
Large-scale public datasets are vital for driving the progress of abstractive summarization,
especially in law, where documents have highly specialized jargon. However, the available …
especially in law, where documents have highly specialized jargon. However, the available …
Comprehensive analysis of knowledge graph embedding techniques benchmarked on link prediction
In knowledge graph representation learning, link prediction is among the most popular and
influential tasks. Its surge in popularity has resulted in a panoply of orthogonal embedding …
influential tasks. Its surge in popularity has resulted in a panoply of orthogonal embedding …
Cogito ergo summ: abstractive summarization of biomedical papers via semantic parsing graphs and consistency rewards
The automatic synthesis of biomedical publications catalyzes a profound research interest
elicited by literature congestion. Current sequence-to-sequence models mainly rely on the …
elicited by literature congestion. Current sequence-to-sequence models mainly rely on the …
Efficient self-supervised metric information retrieval: a bibliography based method applied to COVID literature
G Moro, L Valgimigli - Sensors, 2021 - mdpi.com
The literature on coronaviruses counts more than 300,000 publications. Finding relevant
papers concerning arbitrary queries is essential to discovery helpful knowledge. Current …
papers concerning arbitrary queries is essential to discovery helpful knowledge. Current …