2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 1 cited
Evaluating Dense Passage Retrieval using Transformers
Nima Sadri
Although representational retrieval models based on Transformers have been able to make major advances in the past few years, and despite the widely accepted conventions and best-p…
cs.IR2022★ 2 cited
Continuous Active Learning Using Pretrained Transformers
Nima Sadri, Gordon V. Cormack
Pre-trained and fine-tuned transformer models like BERT and T5 have improved the state of the art in ad-hoc retrieval and question-answering, but not as yet in high-recall informat…
cs.CL2021★ 1 cited
MeetSum: Transforming Meeting Transcript Summarization using Transformers!
Nima Sadri, Bohan Zhang, Bihan Liu
Creating abstractive summaries from meeting transcripts has proven to be challenging due to the limited amount of labeled data available for training neural network models. Moreove…