activity
20182022
most citedRepresentation based meta-learning for few-shot spoken intent recognition

9 citations · 9 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CL2022

Adaptive Discounting of Implicit Language Models in RNN-Transducers

Vinit Unni, Shreya Khare, Ashish Mittal +3

RNN-Transducer (RNN-T) models have become synonymous with streaming end-to-end ASR systems. While they perform competitively on a number of evaluation categories, rare words pose a…

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.AI2021

Capturing Row and Column Semantics in Transformer Based Question Answering over Tables

Michael Glass, Mustafa Canim, Alfio Gliozzo +7

Transformer based architectures are recently used for the task of answering questions over tables. In order to improve the accuracy on this task, specialized pre-training technique…