72 citations · 162 across the 19 of their papers we have counts for
20 papers
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…
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…
DataMagic: Transforming Tabular Data into Data Insight Video
Yupeng Xie, Chen Ma, Zhenyang Wang +6
Data videos integrate dynamic charts, voice narration, and synchronized animations to communicate data insights as temporal narratives, making them an effective medium for improvin…
Adaptive Prompt Embedding Optimization for LLM Jailbreaking
Miles Q. Li, Benjamin C. M. Fung, Boyang Li +2
Existing white-box jailbreak attacks against aligned LLMs typically append discrete adversarial suffixes to the user prompt, which visibly alters the prompt and operates in a combi…
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…
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…
ToxiTrace: Gradient-Aligned Training for Explainable Chinese Toxicity Detection
Boyang Li, Hongzhe Shou, Yuanyuan Liang +2
Existing Chinese toxic content detection methods mainly target sentence-level classification but often fail to provide readable and contiguous toxic evidence spans. We propose \tex…
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…
FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol
Jie Zhu, Yimin Tian, Boyang Li +8
This paper introduces \textbf{FinMCP-Bench}, a novel benchmark for evaluating large language models (LLMs) in solving real-world financial problems through tool invocation of finan…
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…
DeepVIS: Bridging Natural Language and Data Visualization Through Step-wise Reasoning
Zhihao Shuai, Boyan Li, Siyu Yan +2
Although data visualization is powerful for revealing patterns and communicating insights, creating effective visualizations requires familiarity with authoring tools and often dis…
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Bang Liu, Xinfeng Li, Jiayi Zhang +45
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…
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…
nvBench 2.0: Resolving Ambiguity in Text-to-Visualization through Stepwise Reasoning
Tianqi Luo, Chuhan Huang, Leixian Shen +5
Text-to-Visualization (Text2VIS) enables users to create visualizations from natural language queries, making data insights more accessible. However, Text2VIS faces challenges in i…
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…
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…
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…
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…
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…
Are Large Language Models Good Statisticians?
Yizhang Zhu, Shiyin Du, Boyan Li +2
Large Language Models (LLMs) have demonstrated impressive capabilities across a range of scientific tasks including mathematics, physics, and chemistry. Despite their successes, th…