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About Probabilistic Assumptions Matter: Improved Models For Distantly-Supervised Document-Level Question Answering
This document discusses probabilistic assumptions used in distant supervision for document-level question answering. It compares previous probability space and distant supervision assumptions, and shows these assumptions interact. Different configurations provide complementary benefits. A multi-objective model is presented that efficiently combines advantages of multiple assumptions, outperforming previous state-of-the-art models on two datasets.
Detailed Information
| Author: | ['HarishNandan'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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