17 citations · 58 across the 19 of their papers we have counts for
23 papers
InfoSync: Information Synchronization across Multilingual Semi-structured Tables
Siddharth Khincha, Chelsi Jain, Vivek Gupta +2
Information Synchronization of semi-structured data across languages is challenging. For instance, Wikipedia tables in one language should be synchronized across languages. To addr…
Leveraging Data Recasting to Enhance Tabular Reasoning
Aashna Jena, Vivek Gupta, Manish Shrivastava +1
Creating challenging tabular inference data is essential for learning complex reasoning. Prior work has mostly relied on two data generation strategies. The first is human annotati…
Realistic Data Augmentation Framework for Enhancing Tabular Reasoning
Dibyakanti Kumar, Vivek Gupta, Soumya Sharma +1
Existing approaches to constructing training data for Natural Language Inference (NLI) tasks, such as for semi-structured table reasoning, are either via crowdsourcing or fully aut…
Enhancing Tabular Reasoning with Pattern Exploiting Training
Abhilash Reddy Shankarampeta, Vivek Gupta, Shuo Zhang
Recent methods based on pre-trained language models have exhibited superior performance over tabular tasks (e.g., tabular NLI), despite showing inherent problems such as not using…
Unsupervised Contextualized Document Representation
Ankur Gupta, Vivek Gupta
Several NLP tasks need the effective representation of text documents. Arora et. al., 2017 demonstrate that simple weighted averaging of word vectors frequently outperforms neural…
RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing
Vivek Gupta, Akshat Shrivastava, Adithya Sagar +2
While large pre-trained language models accumulate a lot of knowledge in their parameters, it has been demonstrated that augmenting it with non-parametric retrieval-based memory ha…