{"total":34,"rows":[{"id":"2305.03111","title":"Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs","created":"2023-05-04","cited_by_count":688,"area":null},{"id":"2411.07763","title":"Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows","created":"2024-11-12","cited_by_count":232,"area":null},{"id":"2311.07989","title":"Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code","created":"2023-11-14","cited_by_count":62,"area":null},{"id":"2408.05109","title":"A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?","created":"2024-08-09","cited_by_count":56,"area":null},{"id":"2208.10099","title":"Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect","created":"2022-08-22","cited_by_count":47,"area":null},{"id":"2301.07695","title":"EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records","created":"2023-01-16","cited_by_count":45,"area":null},{"id":"2306.04743","title":"ScienceBenchmark: A Complex Real-World Benchmark for Evaluating Natural Language to SQL Systems","created":"2023-06-07","cited_by_count":45,"area":null},{"id":"2310.13659","title":"Benchmarking and Improving Text-to-SQL Generation under Ambiguity","created":"2023-10-20","cited_by_count":34,"area":null},{"id":"2310.17894","title":"Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey","created":"2023-10-27","cited_by_count":27,"area":null},{"id":"2311.01173","title":"CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQL","created":"2023-11-02","cited_by_count":24,"area":null},{"id":"2510.05318","title":"BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation for Large Language Models via Lens of Dynamic Interactions","created":"2025-10-06","cited_by_count":19,"area":null},{"id":"2403.15879","title":"TrustSQL: Benchmarking Text-to-SQL Reliability with Penalty-Based Scoring","created":"2024-03-23","cited_by_count":17,"area":null},{"id":"2504.12110","title":"Towards LLM Agents for Earth Observation","created":"2025-04-16","cited_by_count":17,"area":null},{"id":"2402.08349","title":"Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queries","created":"2024-02-13","cited_by_count":12,"area":null},{"id":"2208.04415","title":"Deep Learning Driven Natural Languages Text to SQL Query Conversion: A Survey","created":"2022-08-08","cited_by_count":11,"area":null},{"id":"2310.00789","title":"Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks","created":"2023-10-01","cited_by_count":10,"area":null},{"id":"2402.02167","title":"Vi(E)va LLM! A Conceptual Stack for Evaluating and Interpreting Generative AI-based Visualizations","created":"2024-02-03","cited_by_count":10,"area":null},{"id":"2406.07860","title":"BookSQL: A Large Scale Text-to-SQL Dataset for Accounting Domain","created":"2024-06-12","cited_by_count":10,"area":null},{"id":"2310.17306","title":"FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language","created":"2023-10-26","cited_by_count":7,"area":null},{"id":"2406.00019","title":"EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Records","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2402.08666","title":"Improving Generalization in Semantic Parsing by Increasing Natural Language Variation","created":"2024-02-13","cited_by_count":4,"area":null},{"id":"2202.04847","title":"A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective","created":"2022-02-10","cited_by_count":3,"area":null},{"id":"2301.04110","title":"Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parsers","created":"2023-01-10","cited_by_count":3,"area":null},{"id":"2405.01588","title":"Towards Unbiased Evaluation of Detecting Unanswerable Questions in EHRSQL","created":"2024-04-29","cited_by_count":3,"area":null},{"id":"2505.19971","title":"Conversational Lexicography: Querying Lexicographic Data on Knowledge Graphs with SPARQL through Natural Language","created":"2025-05-26","cited_by_count":3,"area":null},{"id":"2109.13066","title":"Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions","created":"2021-09-15","cited_by_count":2,"area":null},{"id":"2312.14798","title":"Semantic Parsing for Complex Data Retrieval: Targeting Query Plans vs. SQL for No-Code Access to Relational Databases","created":"2023-12-22","cited_by_count":1,"area":null},{"id":"2504.04363","title":"REFORMER: A ChatGPT-Driven Data Synthesis Framework Elevating Text-to-SQL Models","created":"2025-04-06","cited_by_count":1,"area":null},{"id":"2506.23273","title":"FinStat2SQL: A Text2SQL Pipeline for Financial Statement Analysis","created":"2025-06-29","cited_by_count":1,"area":null},{"id":"2510.27532","title":"SQLSpace: A Representation Space for Text-to-SQL to Discover and Mitigate Robustness Gaps","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2606.28387","title":"Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2312.05448","title":"Domain Adaptation of a State of the Art Text-to-SQL Model: Lessons Learned and Challenges Found","created":"2023-12-09","cited_by_count":0,"area":null},{"id":"2603.23375","title":"Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directions","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2606.12088","title":"Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles","created":"2026-06-10","cited_by_count":0,"area":null}],"next_cursor":null}