200 citations · 671 across the 38 of their papers we have counts for
14 papers · 1 filter
Scientific Claim Verification with VERT5ERINI
Ronak Pradeep, Xueguang Ma, Rodrigo Nogueira +1
This work describes the adaptation of a pretrained sequence-to-sequence model to the task of scientific claim verification in the biomedical domain. We propose VERT5ERINI that expl…
Pretrained Transformers for Text Ranking: BERT and Beyond
Jimmy Lin, Rodrigo Nogueira, Andrew Yates
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in response to a query. Although the most common formulation of text ranking is search, ins…
Can questions summarize a corpus? Using question generation for characterizing COVID-19 research
Gabriela Surita, Rodrigo Nogueira, Roberto Lotufo
What are the latent questions on some textual data? In this work, we investigate using question generation models for exploring a collection of documents. Our method, dubbed corpus…
Lite Training Strategies for Portuguese-English and English-Portuguese Translation
Alexandre Lopes, Rodrigo Nogueira, Roberto Lotufo +1
Despite the widespread adoption of deep learning for machine translation, it is still expensive to develop high-quality translation models. In this work, we investigate the use of…
PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data
Diedre Carmo, Marcos Piau, Israel Campiotti +2
In natural language processing (NLP), there is a need for more resources in Portuguese, since much of the data used in the state-of-the-art research is in other languages. In this…
Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset
Edwin Zhang, Nikhil Gupta, Raphael Tang +8
We present Covidex, a search engine that exploits the latest neural ranking models to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institut…