Papers by Kashif Shah
Neural Network based Extreme Classification and Similarity Models for Product Matching (N18-3)
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| Challenge: | Matching a seller listed item to an appropriate product has become a fundamental step for e-commerce platforms. |
| Approach: | They propose to use a shallow neural network to match a seller's item to an appropriate product . they also propose a similarity approach based on deep siamese network to train and infer product information. |
| Outcome: | The proposed models outperform the baseline models by more than 5% in terms of accuracy and are capable of efficient training and inference. |
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics (2021.tacl-1)
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| Challenge: | Existing fairness metrics quantify the differences in a model’s behaviour across a range of demographic groups. |
| Approach: | They propose to unify existing fairness metrics and compare them to three generalized fairness measures to reveal the connections between them. |
| Outcome: | The proposed measures can be explained by differences in parameter choices, and the results are consistent with previous studies. |
Efficient Classification of Long Documents Using Transformers (2022.acl-short)
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| Challenge: | Several methods have been proposed for classifying long textual documents using Transformers, but there is a lack of consensus on a benchmark to enable a fair comparison among different approaches. |
| Approach: | They propose to use a dataset to evaluate the relative efficacy of various models for long document classification using Transformers. |
| Outcome: | The proposed models outperform simple baseline models and yield inconsistent performance across datasets. |