17 citations · 24 across the 6 of their papers we have counts for
9 papers · 1 filter
SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers
Ameet Deshpande, Md Arafat Sultan, Anthony Ferritto +3
Fine-tuning pre-trained language models (PLMs) achieves impressive performance on a range of downstream tasks, and their sizes have consequently been getting bigger. Since a differ…
Entity-Conditioned Question Generation for Robust Attention Distribution in Neural Information Retrieval
Revanth Gangi Reddy, Md Arafat Sultan, Martin Franz +2
We show that supervised neural information retrieval (IR) models are prone to learning sparse attention patterns over passage tokens, which can result in key phrases including name…
Synthetic Target Domain Supervision for Open Retrieval QA
Revanth Gangi Reddy, Bhavani Iyer, Md Arafat Sultan +5
Neural passage retrieval is a new and promising approach in open retrieval question answering. In this work, we stress-test the Dense Passage Retriever (DPR) -- a state-of-the-art…
Towards Robust Neural Retrieval Models with Synthetic Pre-Training
Revanth Gangi Reddy, Vikas Yadav, Md Arafat Sultan +4
Recent work has shown that commonly available machine reading comprehension (MRC) datasets can be used to train high-performance neural information retrieval (IR) systems. However,…
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training
Revanth Gangi Reddy, Bhavani Iyer, Md Arafat Sultan +5
End-to-end question answering (QA) requires both information retrieval (IR) over a large document collection and machine reading comprehension (MRC) on the retrieved passages. Rece…
Answer Span Correction in Machine Reading Comprehension
Revanth Gangi Reddy, Md Arafat Sultan, Efsun Sarioglu Kayi +3
Answer validation in machine reading comprehension (MRC) consists of verifying an extracted answer against an input context and question pair. Previous work has looked at re-assess…