Papers by Harrison Lundberg
Predicting Entity Salience in Extremely Short Documents (2024.emnlp-industry)
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| Challenge: | False positive: ES is a natural language understanding task that determines which entities are most salient to a passage . Falsity: Popsicle, Frank Epperson and San Francisco are salient entities . |
| Approach: | They propose a lightweight and data-efficient approach for entity salience detection on short documents . they propose he use of a human-labeled dataset to evaluate entity salient on short questions . |
| Outcome: | The proposed approach achieves competitive performance over state-of-the-art models at significant cost and latency advantages. |