activity
20172021
most citedStory Generation from Sequence of Independent Short Descriptions

81 citations · 94 across the 6 of their papers we have counts for

collaborators

18 papers

cs.CL2021

Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages

Tejas Indulal Dhamecha, Rudra Murthy, Samarth Bharadwaj +2

We explore the impact of leveraging the relatedness of languages that belong to the same family in NLP models using multilingual fine-tuning. We hypothesize and validate that multi…

cs.CL2021

Topic Transferable Table Question Answering

Saneem Ahmed Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj +5

Weakly-supervised table question-answering(TableQA) models have achieved state-of-art performance by using pre-trained BERT transformer to jointly encoding a question and a table t…

cs.CL20219 cited

Representation based meta-learning for few-shot spoken intent recognition

Ashish Mittal, Samarth Bharadwaj, Shreya Khare +3

Spoken intent detection has become a popular approach to interface with various smart devices with ease. However, such systems are limited to the preset list of intents-terms or co…

cs.CL2021

AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry

Yannis Katsis, Saneem Chemmengath, Vishwajeet Kumar +8

Recent advances in transformers have enabled Table Question Answering (Table QA) systems to achieve high accuracy and SOTA results on open domain datasets like WikiTableQuestions a…

cs.CL2021

Multilingual and code-switching ASR challenges for low resource Indian languages

Anuj Diwan, Rakesh Vaideeswaran, Sanket Shah +19

Recently, there is increasing interest in multilingual automatic speech recognition (ASR) where a speech recognition system caters to multiple low resource languages by taking adva…

cs.AI2020

Template Controllable keywords-to-text Generation

Abhijit Mishra, Md Faisal Mahbub Chowdhury, Sagar Manohar +2

This paper proposes a novel neural model for the understudied task of generating text from keywords. The model takes as input a set of un-ordered keywords, and part-of-speech (POS)…