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20242026
most citedA Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?

50 citations · 55 across the 11 of their papers we have counts for

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2 papers · 1 filter

cs.CL2025★ 2 cited

Reward-SQL: Boosting Text-to-SQL via Stepwise Execution-Aware Reasoning and Process-Supervised Rewards

Yuxin Zhang, Meihao Fan, Ju Fan +5

Recent advances in large language models (LLMs) trained with reinforcement learning (RL) have improved Text-to-SQL performance. However, RL-based approaches still struggle with com…

cs.CL2024

AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework

Meihao Fan, Ju Fan, Nan Tang +3

Answering natural language (NL) questions about tables, known as Tabular Question Answering (TQA), is crucial because it allows users to quickly and efficiently extract meaningful…