Manali Sharma


2022

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Ranking-Constrained Learning with Rationales for Text Classification
Juanyan Wang | Manali Sharma | Mustafa Bilgic
Findings of the Association for Computational Linguistics: ACL 2022

We propose a novel approach that jointly utilizes the labels and elicited rationales for text classification to speed up the training of deep learning models with limited training data. We define and optimize a ranking-constrained loss function that combines cross-entropy loss with ranking losses as rationale constraints. We evaluate our proposed rationale-augmented learning approach on three human-annotated datasets, and show that our approach provides significant improvements over classification approaches that do not utilize rationales as well as other state-of-the-art rationale-augmented baselines.

2015

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Active Learning with Rationales for Text Classification
Manali Sharma | Di Zhuang | Mustafa Bilgic
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies