Papers by Oishik Chatterjee
WARM: A Weakly (+Semi) Supervised Math Word Problem Solver (2022.coling-1)
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| Challenge: | Existing approaches to solving math word problems require full supervision in the form of intermediate equations. |
| Approach: | They propose a weakly supervised model that requires only the final answer as supervision to solve math word problems. |
| Outcome: | The proposed model achieves accuracy gains of 4.5% and 32% over current weakly-supervised methods on standard Math23K and AllArith datasets. |
Semi-Supervised Data Programming with Subset Selection (2021.findings-acl)
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| Challenge: | Several approaches to improve annotation cost have been proposed to use large amounts of labelled training data. |
| Approach: | They propose a semi-supervised data programming paradigm that uses weak supervision and semi-supervised loss functions to augment small amounts of labelled data with a large unlabelled dataset. |
| Outcome: | The proposed framework outperforms the current state-of-the-art on seven publicly available datasets. |