{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T15:53:18Z","timestamp":1765295598744,"version":"3.45.0"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227747","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-9","source":"Crossref","is-referenced-by-count":1,"title":["End-to-End Text-to-SQL with Dataset Selection: Leveraging LLMs for Adaptive Query Generation"],"prefix":"10.1109","author":[{"given":"Anurag","family":"Tripathi","sequence":"first","affiliation":[{"name":"Infoorigin Pvt Ltd, Data Science"}]},{"given":"Vaibhav","family":"Patle","sequence":"additional","affiliation":[{"name":"Infoorigin Pvt Ltd, Data Science"}]},{"given":"Abhinav","family":"Jain","sequence":"additional","affiliation":[{"name":"Infoorigin Pvt Ltd, Data Science"}]},{"given":"Ayush","family":"Pundir","sequence":"additional","affiliation":[{"name":"Infoorigin Pvt Ltd, Data Science"}]},{"given":"Sairam","family":"Menon","sequence":"additional","affiliation":[{"name":"J&amp;J Innovative Medicine Technology R&amp;D,USA"}]},{"given":"Ajeet Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"Infoorigin Pvt Ltd, Data Science"}]},{"given":"Dorien","family":"Herremans","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design,Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.14778\/3641204.3641221"},{"key":"ref2","article-title":"Din-SQL: Decomposed in-context learning of text-to-SQL with self-correction","volume":"36","author":"Pourreza","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"PETSQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Crossconsistency","year":"2024","author":"Li","key":"ref3"},{"article-title":"Benchmarking the text-to-SQL capability of large language models: A comprehensive evaluation","year":"2024","author":"Zhang","key":"ref4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-68309-1_11"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-62495-7_12"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457543"},{"article-title":"A survey on text-to-SQL parsing: Concepts, methods, and future directions","year":"2022","author":"Qin","key":"ref8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3318464.3389776"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1561\/1900000078"},{"issue":"12","key":"ref11","first-page":"2747","article-title":"Athena++ natural language querying for complex nested SQL queries","volume-title":"Proc. of the VLDB Endowment","volume":"13","author":"Sen"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/553"},{"article-title":"Addressing limitations of encoder-decoder based approach to text-to-SQL","volume-title":"Proc. of the 29th Int. Conf. on Computational Linguistics","author":"Popescu","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.211"},{"key":"ref15","article-title":"Roberta: A robustly optimized bert pretraining approach","volume":"364","author":"Liu","year":"2019"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.99"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1444"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1425"},{"article-title":"Learning to parse database queries using inductive logic programming","volume-title":"Proc. of the national Conf. on artificial intelligence","author":"Zelle","key":"ref19"},{"article-title":"CHESS: Contextual Harnessing for Efficient SQL Synthesis","year":"2024","author":"Talaei","key":"ref20"},{"article-title":"Evaluating the text-to-SQL capabilities of large language models","year":"2022","author":"Rajkumar","key":"ref21"},{"key":"ref22","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"35","author":"Wei","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"Mac-SQL: A multi-agent collaborative framework for text-to-SQL","volume-title":"Proc. of the 31st Int. Conf. on Computational Linguistics","author":"Wang","key":"ref23"},{"article-title":"C3: Zero-shot text-to-SQL with chatgpt","year":"2023","author":"Dong","key":"ref24"},{"article-title":"Openagents: An open platform for language agents in the wild","year":"2023","author":"Xie","key":"ref25"},{"article-title":"Autogen: Enabling next-gen llm applications via multi-agent conversation framework","year":"2023","author":"Wu","key":"ref26"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-024-40231-1"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i22.34511"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i11.26535"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.86"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i11.26536"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/SLT54892.2023.10023434"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.211"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.779"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.174"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00403"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.29"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227747.pdf?arnumber=11227747","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:25:25Z","timestamp":1763191525000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227747\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227747","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}