1 code implementation • NAACL (CALCS) 2021 • Devansh Gautam, Kshitij Gupta, Manish Shrivastava
To translate English-Hindi code-mixed data to English, we use mBART, a pre-trained multilingual sequence-to-sequence model that has shown competitive performance on various low-resource machine translation pairs and has also shown performance gains in languages that were not in its pre-training corpus.
1 code implementation • NAACL (CALCS) 2021 • Devansh Gautam, Prashant Kodali, Kshitij Gupta, Anmol Goel, Manish Shrivastava, Ponnurangam Kumaraguru
Code-mixed languages are very popular in multilingual societies around the world, yet the resources lag behind to enable robust systems on such languages.
no code implementations • ACL 2022 • Samyak Agrawal, Kshitij Gupta, Devansh Gautam, Radhika Mamidi
Political propaganda in recent times has been amplified by media news portals through biased reporting, creating untruthful narratives on serious issues causing misinformed public opinions with interests of siding and helping a particular political party.
1 code implementation • 7 Jun 2022 • Kshitij Gupta, Devansh Gautam, Radhika Mamidi
We propose a pipeline that utilizes English-only vision-language models to train a monolingual model for a target language.
1 code implementation • Workshop on Asian Translation 2021 • Kshitij Gupta, Devansh Gautam, Radhika Mamidi
Multimodal Machine Translation (MMT) enriches the source text with visual information for translation.
Ranked #1 on
Multimodal Machine Translation
on Hindi Visual Genome (Test Set)
(using extra training data)
1 code implementation • SEMEVAL 2021 • Kshitij Gupta, Devansh Gautam, Radhika Mamidi
Memes are one of the most popular types of content used to spread information online.
1 code implementation • SEMEVAL 2021 • Devansh Gautam, Kshitij Gupta, Manish Shrivastava
We fine-tune TAPAS (a model which extends BERT's architecture to capture tabular structure) for both the subtasks as it has shown state-of-the-art performance in various table understanding tasks.