118 citations · 137 across the 17 of their papers we have counts for
8 papers · 1 filter
Agent-Kernel: A MicroKernel Multi-Agent System Framework for Adaptive Social Simulation Powered by LLMs
Yuren Mao, Peigen Liu, Xinjian Wang +11
Multi-Agent System (MAS) developing frameworks serve as the foundational infrastructure for social simulations powered by Large Language Models (LLMs). However, existing frameworks…
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering
Yuren Mao, Wenyi Xu, Yuyang Qin +1
Computed Tomography (CT) scan, which produces 3D volumetric medical data that can be viewed as hundreds of cross-sectional images (a.k.a. slices), provides detailed anatomical info…
Text-to-Pipeline: Bridging Natural Language and Data Preparation Pipelines
Yuhang Ge, Yachuan Liu, Zhangyan Ye +2
Data preparation (DP) transforms raw data into a form suitable for downstream applications, typically by composing operations into executable pipelines. Building such pipelines is…
Birdie: Natural Language-Driven Table Discovery Using Differentiable Search Index
Yuxiang Guo, Zhonghao Hu, Yuren Mao +3
Natural language (NL)-driven table discovery identifies relevant tables from large table repositories based on NL queries. While current deep-learning-based methods using the tradi…
scAgent: Universal Single-Cell Annotation via a LLM Agent
Yuren Mao, Yu Mi, Peigen Liu +3
Cell type annotation is critical for understanding cellular heterogeneity. Based on single-cell RNA-seq data and deep learning models, good progress has been made in annotating a f…
SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation
Jiahui Li, Tongwang Wu, Yuren Mao +3
High quality SQL corpus is essential for intelligent database. For example, Text-to-SQL requires SQL queries and correspond natural language questions as training samples. However,…
DAgent: A Relational Database-Driven Data Analysis Report Generation Agent
Wenyi Xu, Yuren Mao, Xiaolu Zhang +4
Relational database-driven data analysis (RDB-DA) report generation, which aims to generate data analysis reports after querying relational databases, has been widely applied in fi…
Snoopy: Effective and Efficient Semantic Join Discovery via Proxy Columns
Yuxiang Guo, Yuren Mao, Zhonghao Hu +2
Semantic join discovery, which aims to find columns in a table repository with high semantic joinabilities to a query column, is crucial for dataset discovery. Existing methods can…