activity
20222025
most citedCan LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

87 citations · 180 across the 9 of their papers we have counts for

collaborators

10 papers

cs.DB2025

SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications

Jinyang Li, Xiaolong Li, Ge Qu +17

Resolution of complex SQL issues persists as a significant bottleneck in real-world database applications. Current Large Language Models (LLMs), while adept at text-to-SQL translat…

cs.CL2025

Micro-Act: Mitigating Knowledge Conflict in LLM-based RAG via Actionable Self-Reasoning

Nan Huo, Jinyang Li, Bowen Qin +5

Retrieval-Augmented Generation (RAG) systems commonly suffer from Knowledge Conflicts, where retrieved external knowledge contradicts the inherent, parametric knowledge of large la…

cs.CL2025

SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQL

Ge Qu, Jinyang Li, Bowen Qin +4

Current self-correction approaches in text-to-SQL face two critical limitations: 1) Conventional self-correction methods rely on recursive self-calls of LLMs, resulting in multipli…

cs.CL2024★ 1 cited

Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation

Ge Qu, Jinyang Li, Bowen Li +4

Large Language Models (LLMs) driven by In-Context Learning (ICL) have significantly improved the performance of text-to-SQL. Previous methods generally employ a two-stage reasoning…

cs.AI2024

Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

Jinyang Li, Nan Huo, Yan Gao +7

Interactive Data Analysis, the collaboration between humans and LLM agents, enables real-time data exploration for informed decision-making. The challenges and costs of collecting…

cs.CL2024★ 55 cited

A Survey on Knowledge Distillation of Large Language Models

Xiaohan Xu, Ming Li, Chongyang Tao +6

In the era of Large Language Models (LLMs), Knowledge Distillation (KD) emerges as a pivotal methodology for transferring advanced capabilities from leading proprietary LLMs, such…

cs.CL2023

Causal Document-Grounded Dialogue Pre-training

Yingxiu Zhao, Bowen Yu, Haiyang Yu +6

The goal of document-grounded dialogue (DocGD) is to generate a response by grounding the evidence in a supporting document in accordance with the dialogue context. This process in…

cs.CL2023★ 87 cited

Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

Jinyang Li, Binyuan Hui, Ge Qu +15

Text-to-SQL parsing, which aims at converting natural language instructions into executable SQLs, has gained increasing attention in recent years. In particular, Codex and ChatGPT…

cs.CL2023★ 7 cited

Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing

Jinyang Li, Binyuan Hui, Reynold Cheng +7

The task of text-to-SQL parsing, which aims at converting natural language questions into executable SQL queries, has garnered increasing attention in recent years, as it can assis…

cs.CL2022★ 30 cited

A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions

Bowen Qin, Binyuan Hui, Lihan Wang +9

Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is to convert a natural language (NL) question to its corresponding structured query langu…