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20242026
most citedThe Dawn of Natural Language to SQL: Are We Fully Ready?

72 citations · 162 across the 19 of their papers we have counts for

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12 papers · 1 filter

cs.DB2026

MIRA: Evidence-Verified Repair Memory for Text-to-SQL Correction

Yining Liu, Chenyu Yang, Boyan Li +2

Text-to-SQL agents still produce executable yet semantically incorrect SQL. A reliable SQL corrector must repair incorrect queries without corrupting correct ones. Confirmed correc…

cs.DB2026

SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration

Yizhang Zhu, Zhangyang Peng, Boyan Li +1

Text-to-SQL enables users to access relational databases via natural language, but real-world settings remain challenging due to coordinated reasoning over complex database environ…

cs.DB2026

DPC: Training-Free Text-to-SQL Candidate Selection via Dual-Paradigm Consistency

Boyan Li, Ou Ocean Kun Hei, Yue Yu +1

While Large Language Models (LLMs) demonstrate impressive proficiency in generating SQL queries, they fundamentally lack the capability to self-evaluate correctness without an exec…

cs.DB2026

ROSE: An Intent-Centered Evaluation Metric for NL2SQL

Wenqi Pei, Shizheng Hou, Boyan Li +3

Execution Accuracy (EX), the widely used metric for evaluating the effectiveness of Natural Language to SQL (NL2SQL) solutions, is becoming increasingly unreliable. It is sensitive…

cs.DB2026★ 1 cited

DeepEye: A Steerable Self-driving Data Agent System

Boyan Li, Yiran Peng, Yupeng Xie +5

Large Language Models (LLMs) have revolutionized natural language interaction with data. The "holy grail" of data analytics is to build autonomous Data Agents that can self-drive c…

cs.DB2025

DeepEye-SQL: A Software-Engineering-Inspired Text-to-SQL Framework

Boyan Li, Chong Chen, Zhujun Xue +2

Large language models (LLMs) have advanced Text-to-SQL, yet existing solutions still fall short of system-level reliability. The limitation is not merely in individual modules -- e…

cs.DB2025

EllieSQL: Cost-Efficient Text-to-SQL with Complexity-Aware Routing

Yizhang Zhu, Runzhi Jiang, Boyan Li +2

Text-to-SQL automatically translates natural language queries to SQL, allowing non-technical users to retrieve data from databases without specialized SQL knowledge. Despite the su…

cs.DB2025★ 17 cited

NL2SQL-BUGs: A Benchmark for Detecting Semantic Errors in NL2SQL Translation

Xinyu Liu, Shuyu Shen, Boyan Li +2

Natural Language to SQL (i.e., NL2SQL) translation is crucial for democratizing database access, but even state-of-the-art models frequently generate semantically incorrect SQL que…

cs.DB2025★ 1 cited

Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search

Boyan Li, Jiayi Zhang, Ju Fan +4

Text-to-SQL, which enables natural language interaction with databases, serves as a pivotal method across diverse industries. With new, more powerful large language models (LLMs) e…

cs.DB2024★ 1 cited

A Plug-and-Play Natural Language Rewriter for Natural Language to SQL

Peixian Ma, Boyan Li, Runzhi Jiang +3

Existing Natural Language to SQL (NL2SQL) solutions have made significant advancements, yet challenges persist in interpreting and translating NL queries, primarily due to users' l…

cs.DB2024★ 50 cited

A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?

Xinyu Liu, Shuyu Shen, Boyan Li +7

Translating users' natural language queries (NL) into SQL queries (i.e., Text-to-SQL, a.k.a. NL2SQL) can significantly reduce barriers to accessing relational databases and support…

cs.DB2024★ 72 cited

The Dawn of Natural Language to SQL: Are We Fully Ready?

Boyan Li, Yuyu Luo, Chengliang Chai +2

Translating users' natural language questions into SQL queries (i.e., NL2SQL) significantly lowers the barriers to accessing relational databases. The emergence of Large Language M…