Papers by Kunal Chawla

2 papers
Semi-supervised Formality Style Transfer using Language Model Discriminator and Mutual Information Maximization (2020.findings-emnlp)

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Challenge: Formality style transfer is the task of converting informal sentences to grammatically-correct formal sentences.
Approach: They propose a semi-supervised formality style transfer model that utilizes a language model-based discriminator to maximize the likelihood of the output sentence being formal.
Outcome: The proposed model outperforms state-of-the-art models in terms of automated metrics and human judgement.
When FLUE Meets FLANG: Benchmarks and Large Pretrained Language Model for Financial Domain (2022.emnlp-main)

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Challenge: Pre-trained language models have shown impressive performance on a variety of tasks and domains.
Approach: They propose a domain specific financial LANGuage model which uses financial keywords and phrases for better masking.
Outcome: The proposed model outperforms existing models on a variety of tasks and domains.

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