Papers with precision-recall tradeoff
Supervised Open Information Extraction (N18-1)
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| Challenge: | Existing methods for Open Information Extraction (Open IE) use semisupervised approaches or rule-based algorithms. |
| Approach: | They propose a supervised approach to Open Information Extraction (Open IE) they build on recent deep Semantic Role Labeling models to extract Open IE tuples . |
| Outcome: | The proposed model outperforms state-of-the-art Open IE systems on benchmark datasets. |
Divide, Link, and Conquer: Recall-oriented Schema Linking for NL-to-SQL via Question Decomposition (2025.emnlp-industry)
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| Challenge: | Open-source LLMs often depend on large proprietary models, which introduce serious privacy concerns. |
| Approach: | They propose a plug-and-play framework that improves SQL generation for smaller LLMs . they propose to apply question decomposition at the schema linking stage rather than during SQL generation . |
| Outcome: | The proposed framework improves schema linking recall by 25.1% and execution accuracy by 8.2% on the BIRD benchmark. |