Papers with variational EM
Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision (D18-1)
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| Challenge: | Indirect supervision is a promising direction to address the annotation bottleneck . end-to-end modeling with probabilistic logic is often intractable due to inference and learning . |
| Approach: | They propose a framework for indirect supervision that integrates deep learning with deep learning by combining probabilistic logic with deep-learning. |
| Outcome: | Experiments on biomedical machine reading demonstrate the potential of this framework. |
Modular Self-Supervision for Document-Level Relation Extraction (2021.emnlp-main)
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| Challenge: | Prior work on information extraction tends to focus on binary relations within sentences . practical applications often require extracting complex relations across large text spans . |
| Approach: | They propose to decompose document-level relation extraction into relation detection and argument resolution, taking inspiration from Davidsonian semantics. |
| Outcome: | The proposed method outperforms state-of-the-art methods in biomedical machine reading for precision oncology by 20 absolute F1 points. |