3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 1 cited
GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering
Dhaval Taunk, Lakshya Khanna, Pavan Kandru +3
Commonsense question-answering (QA) methods combine the power of pre-trained Language Models (LM) with the reasoning provided by Knowledge Graphs (KG). A typical approach collects…
cs.CL2023
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages
Dhaval Taunk, Shivprasad Sagare, Anupam Patil +3
Lack of encyclopedic text contributors, especially on Wikipedia, makes automated text generation for low resource (LR) languages a critical problem. Existing work on Wikipedia text…
cs.CL2023★ 3 cited
Summarizing Indian Languages using Multilingual Transformers based Models
Dhaval Taunk, Vasudeva Varma
With the advent of multilingual models like mBART, mT5, IndicBART etc., summarization in low resource Indian languages is getting a lot of attention now a days. But still the numbe…