The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers
Open accessAbstract
When translating natural language questions into SQL queries to answer questions from a database, contemporary semantic parsing models struggle to generalize to unseen database schemas.The generalization challenge lies in (a) encoding the database relations in an accessible way for the semantic parser, and (b) modeling alignment between database columns and their mentions in a given query.We present a unified framework, based on the relation-aware self-attention mechanism, to address schema encoding, schema linking, and feature representation within a text-to-SQL encoder.On the challenging Spider dataset this framework boosts the exact match accuracy to 57.2%, surpassing its best counterparts by 8.7% absolute improvement.Further augmented with BERT, it achieves the new state-of-the-art performance of 65.6% on the Spider leaderboard.In addition, we observe qualitative improvements in the model's understanding of schema linking and alignment.Our implementation will be open-sourced at https://github.com/Microsoft/rat-sql.
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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Multimodal learning with transformers: A survey
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TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
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Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Gao, D., Wang, H., Li, Y., Sun, X., Qian, Y., Ding, B., & Zhou, J. (2023) · arXiv · doi:10.48550/arxiv.2308.15363 · Cited by 485
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
Scholak, T., Schucher, N., & Bahdanau, D. (2021) · arXiv · doi:10.48550/arxiv.2109.05093 · Cited by 346
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models
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Metadata
- Authors
- Wang, B., Shin, R., Liu, X., Polozov, O., & Richardson, M.
- Venue
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Published
- 2020
- Pages
- 7567-7578
- OpenAlex
- W2985377636
- Cited by
- 512
- References
- 33
- FWCI
- 26.10
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- Wang, B., Shin, R., Liu, X., Polozov, O., & Richardson, M. (2020). RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.677
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