Papers by Yuanyi Ji
Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruning (2024.emnlp-main)
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| Challenge: | Existing methods for text-to-SQL semantic parsing are limited to retrieving schemata based on a single query. |
| Approach: | They propose a text-to-sql semantic parser that uses abstract syntax trees to select few-shot examples for retrieval-augmented generation. |
| Outcome: | The proposed model can generate approximated versions of SQL queries in parallel, and shows improvements over state-of-the-art benchmarks. |