Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL | Paper Citation Record

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This paper cites FANNO : Augmenting High-Quality Instruction Data with Open-Sourced LLM s Only.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL FANNO : Augmenting High-Quality Instruction Data with Open-Sourced LLM s Only

Reference 1

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This paper cites Tag-Instruct: Controlled Instruction Complexity Enhancement through Structure-based Augmentation.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Tag-Instruct: Controlled Instruction Complexity Enhancement through Structure-based Augmentation

Reference 2

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This paper cites BiasScope: Towards Automated Detection of Bias in.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL BiasScope: Towards Automated Detection of Bias in

Reference 3

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This paper cites Pi- SQL : Enhancing Text-to- SQL with Fine-Grained Guidance from Pivot Programming Languages.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Pi- SQL : Enhancing Text-to- SQL with Fine-Grained Guidance from Pivot Programming Languages

Reference 4

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This paper cites Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 5

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This paper cites 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 , pages=

Reference 6

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This paper cites Companion Proceedings of the ACM on Web Conference 2025 , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Companion Proceedings of the ACM on Web Conference 2025 , pages=

Reference 7

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This paper cites arXiv preprint arXiv:2403.02951 , year=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL arXiv preprint arXiv:2403.02951 , year=

Reference 8

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This paper cites Gemma 3 Technical Report.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Gemma 3 Technical Report

Reference 9

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This paper cites CoRR , volume =.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL CoRR , volume =

Reference 10

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Unresolved cited work

Reference 11

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This paper cites Transfer Learning for Natural Language Processing Workshop , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Transfer Learning for Natural Language Processing Workshop , pages=

Reference 12

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This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 13

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This paper cites Advances in Neural Information Processing Systems , volume=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Advances in Neural Information Processing Systems , volume=

Reference 14

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Unresolved cited work

Reference 15

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This paper cites Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Reference 16

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This paper cites Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 17

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This paper cites arXiv preprint arXiv:2501.09310 , year=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL arXiv preprint arXiv:2501.09310 , year=

Reference 18

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL arXiv preprint arXiv:2508.15276 , year=

Reference 19

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2025 , url=

Reference 20

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This paper cites GPT-4o System Card.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL GPT-4o System Card

Reference 21

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Natural language engineering , volume=

Reference 22

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the VLDB Endowment , volume=

Reference 23

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This paper cites Advances in Neural Information Processing Systems , volume=.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Advances in Neural Information Processing Systems , volume=

Reference 24

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This paper cites EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructions.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructions

Reference 25

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 26

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2015 2nd international conference on electrical information and communication technologies (EICT) , pages=

Reference 27

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This paper cites Hybrid Ranking Network for Text-to-SQL.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Hybrid Ranking Network for Text-to-SQL

Reference 28

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2025 , publisher =

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This paper cites Qwen3 Technical Report.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Qwen3 Technical Report

Reference 30

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 31

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This paper cites Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-

Reference 32

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Computational Linguistics , volume=

Reference 33

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

Reference 34

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 35

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages=

Reference 36

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL ACM Comput

Reference 37

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Advances in Neural Information Processing Systems , volume=

Reference 38

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2025 , eprint=

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities

Reference 40

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL

Reference 41

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2024 International Joint Conference on Neural Networks (IJCNN) , pages=

Reference 42

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Unresolved cited work

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL ICLR 2025 Workshop: VerifAI: AI Verification in the Wild , year=

Reference 44

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale

Reference 45

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL SHARE : An SLM -based Hierarchical Action C or RE ction Assistant for Text-to- SQL

Reference 46

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL SQLF orge: Synthesizing Reliable and Diverse Data to Enhance Text-to- SQL Reasoning in LLM s

Reference 47

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Proceedings of the ACM on Management of Data , volume=

Reference 48

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 49

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL 2024 IEEE Calcutta Conference (CALCON) , pages=

Reference 50

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective

Reference 51

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL arXiv preprint arXiv:2505.12185 , year=

Reference 52

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs

Reference 53

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Emoti-Attack: Zero-Perturbation Adversarial Attacks on NLP Systems via Emoji Sequences

Reference 54

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL

Reference 55

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL Automatic Metadata Extraction for Text-to-SQL

Reference 56

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Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL

Reference 57

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Reference 72

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Reference 83

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