Papers by Abhijit Mahabal

2 papers
Text Classification with Few Examples using Controlled Generalization (N19-1)

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Challenge: Current training data for text classification is limited, resulting in limited generalization capacity.
Approach: They propose a feed-forward network that can generalize from unlabeled parsed corpora to produce task-specific semantic vectors.
Outcome: The proposed approach is especially effective in low-data scenarios compared to state-of-the-art methods.
How Large Are Lions? Inducing Distributions over Quantitative Attributes (P19-1)

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Challenge: Current NLP systems have little knowledge about quantitative attributes of objects and events.
Approach: They propose to use web data to create a resource consisting of distributions over physical quantities associated with objects, adjectives, and verbs.
Outcome: The proposed method compares favorably with state-of-the-art results on existing datasets for relative comparisons of nouns and adjectives and on a new dataset.

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