16 citations · 43 across the 8 of their papers we have counts for
10 papers
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…
MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding
Revanth Gangi Reddy, Xilin Rui, Manling Li +9
Recently, there has been an increasing interest in building question answering (QA) models that reason across multiple modalities, such as text and images. However, QA using images…
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,…
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27
Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…
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…
Pushing the Limits of AMR Parsing with Self-Learning
Young-Suk Lee, Ramon Fernandez Astudillo, Tahira Naseem +3
Abstract Meaning Representation (AMR) parsing has experienced a notable growth in performance in the last two years, due both to the impact of transfer learning and the development…
Multi-Stage Pre-training for Low-Resource Domain Adaptation
Rong Zhang, Revanth Gangi Reddy, Md Arafat Sultan +7
Transfer learning techniques are particularly useful in NLP tasks where a sizable amount of high-quality annotated data is difficult to obtain. Current approaches directly adapt a…
Edge Replacement Grammars: A Formal Language Approach for Generating Graphs
Revanth Reddy, Sarath Chandar, Balaraman Ravindran
Graphs are increasingly becoming ubiquitous as models for structured data. A generative model that closely mimics the structural properties of a given set of graphs has utility in…
Multi-level Memory for Task Oriented Dialogs
Revanth Reddy, Danish Contractor, Dinesh Raghu +1
Recent end-to-end task oriented dialog systems use memory architectures to incorporate external knowledge in their dialogs. Current work makes simplifying assumptions about the str…
FigureNet: A Deep Learning model for Question-Answering on Scientific Plots
Revanth Reddy, Rahul Ramesh, Ameet Deshpande +1
Deep Learning has managed to push boundaries in a wide variety of tasks. One area of interest is to tackle problems in reasoning and understanding, with an aim to emulate human int…