Feifei Pan — accepted AI-conference papers

2023

Multi-Row, Multi-Span Distant Supervision For Table+Text Question Answering

Vishwajeet Kumar, Yash Gupta, Saneem Chemmengath, Jaydeep Sen, Soumen Chakrabarti, Samarth Bharadwaj +1

ACL 2023long

Question answering (QA) over tables and linked text, also called TextTableQA, has witnessed significant research in recent years, as tables are often found embedded in documents along with related text. HybridQA and OTT-QA are the two best-known TextTableQA datasets, with questions that are best ans…

Cited by 6 Source ↗PDF ↗Scholar ↗

2022

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

Yannis Katsis, Saneem Chemmengath, Vishwajeet Kumar, Samarth Bharadwaj, Mustafa Canim, Michael Glass +5

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…

Cited by 40 Source ↗PDF ↗code ↗Scholar ↗

2021

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

Michael Glass, Mustafa Canim, Alfio Gliozzo, Saneem Chemmengath, Vishwajeet Kumar, Rishav Chakravarti +4

NAACL 2021long

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 techniques have been developed and applied on millions of open-domain web tables. In this paper, we propose two novel approaches…

Cited by 18 Source ↗PDF ↗code ↗Scholar ↗