Papers by Sandeep Mathias
ASAP++: Enriching the ASAP Automated Essay Grading Dataset with Essay Attribute Scores (L18-1)
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| Challenge: | Automated essay grading (AEG) is one of the most challenging activities in natural language processing (NLP). |
| Approach: | They propose to annotate the ASAP AEG dataset and use it to score different attributes of the essays. |
| Outcome: | The proposed resource is based on the ASAP++ dataset, which contains scores for different attributes of the essays, such as content, word choice, organization, sentence fluency, etc. |
Many Hands Make Light Work: Using Essay Traits to Automatically Score Essays (2022.naacl-main)
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| Challenge: | In automatic essay grading, essay traits are important for scoring the essay holistically . a single-task learning system gives the best results for scoring essays holistically and scoring essay traits. |
| Approach: | They propose a way to score essays using a multi-task learning approach . they compare the MTL-based BiLSTM system to a single-task Learning approach based on LSTMs and BiLStms . |
| Outcome: | The proposed system gives better results for scoring essay holistically and scoring essay traits. |
Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour (P18-1)
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Sandeep Mathias, Diptesh Kanojia, Kevin Patel, Samarth Agrawal, Abhijit Mishra, Pushpak Bhattacharyya
| Challenge: | Existing methods to predict text quality include estimating subjective aspects of text, like structure, clarity, etc. |
| Approach: | They propose to capture gaze behaviour to help predict text quality by reporting improvements obtained by adding gaze features to traditional textual features for score prediction. |
| Outcome: | The proposed model shows that capturing gaze behaviour improves the accuracy of score prediction when the reader has fully understood the text. |
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour (2020.aacl-main)
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| Challenge: | Using gaze behaviour to solve automatic essay grading tasks is costly in terms of time and money. |
| Approach: | They propose to collect gaze behaviour from 48 essays and learn gaze behaviour for the rest of the essays using a multi-task learning framework. |
| Outcome: | The proposed approach achieves a statistically significant improvement over the state-of-the-art system for the essay sets where gaze data is available. |