Search Results for author: Sagnik Mukherjee

Found 6 papers, 2 papers with code

AUTOSUMM: Automatic Model Creation for Text Summarization

no code implementations EMNLP 2021 Sharmila Reddy Nangi, Atharv Tyagi, Jay Mundra, Sagnik Mukherjee, Raj Snehal, Niyati Chhaya, Aparna Garimella

Recent efforts to develop deep learning models for text generation tasks such as extractive and abstractive summarization have resulted in state-of-the-art performances on various datasets.

Abstractive Text Summarization Knowledge Distillation +2

On the Robustness of Reading Comprehension Models to Entity Renaming

1 code implementation NAACL 2022 Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren

We study the robustness of machine reading comprehension (MRC) models to entity renaming -- do models make more wrong predictions when the same questions are asked about an entity whose name has been changed?

Continual Pretraining Machine Reading Comprehension

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