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Karthik Sankaranarayanan

6 accepted papers

2022

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

NAACL 2022industry

Table Question Answering (Table QA) systems have been shown to be highly accurate when trained and tested on open-domain datasets built on top of Wikipedia tables. However, it is not clear whether their performance remains the same when applied to domain-specific scientific and business documents, e…

2021

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

EMNLP 2021main

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 multilingual fine-tuning of pre-trained language models can yield better performance on downstream NLP applications, compared…

2021

Topic Transferable Table Question Answering

EMNLP 2021main

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 to produce structured query for the question. However, in practical settings TableQA systems are deployed over table cor…

2020

Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings

COLING 2020main

Natural Language Query interfaces allow the end-users to access the desired information without the need to know any specialized query language, data storage, or schema details. Even with the recent advances in NLP research space, the state-of-the-art QA systems fall short of understanding implicit…

2018

DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension

ICLR 2018workshop

We propose DuoRC, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by existing RC datasets. DuoRC contains 186,089 unique question-answer pairs created from a collection of 7680 pairs of movie pl…

Cited by 161SourcecodeScholar
2018

On Controllable Sparse Alternatives to Softmax

NeurIPS 2018poster

Converting an n-dimensional vector to a probability distribution over n objects is a commonly used component in many machine learning tasks like multiclass classification, multilabel classification, attention mechanisms etc. For this, several probability mapping functions have been proposed and empl…

Cited by 76SourcePDFScholar