69 citations · 87 across the 6 of their papers we have counts for
10 papers
CST5: Data Augmentation for Code-Switched Semantic Parsing
Anmol Agarwal, Jigar Gupta, Rahul Goel +3
Extending semantic parsers to code-switched input has been a challenging problem, primarily due to a lack of supervised training data. In this work, we introduce CST5, a new data a…
TableFormer: Robust Transformer Modeling for Table-Text Encoding
Jingfeng Yang, Aditya Gupta, Shyam Upadhyay +3
Understanding tables is an important aspect of natural language understanding. Existing models for table understanding require linearization of the table structure, where row or co…
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Lianhui Qin, Aditya Gupta, Shyam Upadhyay +3
Everyday conversations require understanding everyday events, which in turn, requires understanding temporal commonsense concepts interwoven with those events. Despite recent progr…
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Aditya Gupta, Jiacheng Xu, Shyam Upadhyay +2
Disfluencies is an under-studied topic in NLP, even though it is ubiquitous in human conversation. This is largely due to the lack of datasets containing disfluencies. In this pape…
Attention Interpretability Across NLP Tasks
Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar +1
The attention layer in a neural network model provides insights into the model's reasoning behind its prediction, which are usually criticized for being opaque. Recently, seemingly…
Bootstrapping Transliteration with Constrained Discovery for Low-Resource Languages
Shyam Upadhyay, Jordan Kodner, Dan Roth
Generating the English transliteration of a name written in a foreign script is an important and challenging step in multilingual knowledge acquisition and information extraction.…