Summary of Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion, by Juhwan Choi et al.
Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion
by Juhwan Choi, YoungBin Kim
First submitted to arxiv on: 29 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel text data augmentation strategy is proposed to avoid losing original semantics in real-world applications. By deleting adverbs, which play a subsidiary role in sentences, the approach efficiently and effectively preserves semantic meaning for tasks like single text classification and natural language inference. Comprehensive experiments demonstrate its efficiency and effectiveness, with publicly released source code available for reproducibility. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way to make text data more useful is being developed. Right now, people often use rules to change text, which can be good because it’s cheap. But sometimes this method loses the original meaning of what was written. To fix this, researchers came up with a new idea: just delete the words that don’t really matter (like adverbs). This works well for things like recognizing what kind of text something is and understanding its meaning. |
Keywords
» Artificial intelligence » Data augmentation » Inference » Semantics » Text classification
