每日文献雷达

2026-07-12

今日入选

• Classifier-Augmented Generation for Structured Workflow Prediction（topic keywords matched; 2 citations）
• SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads（5 citations）
• QUIS: Question-guided Insights Generation for Automated Exploratory Data Analysis（topic keywords matched; 2 citations）
• OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System（topic keywords matched; code signal; 16 citations; appeared 2x before）
• IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpus（code signal; 19 citations; appeared 1x before）

1. Classifier-Augmented Generation for Structured Workflow Prediction

        - **来源**：deepxiv
        - **分数**：0.3944
        - **入选原因**：topic keywords matched; 2 citations
        - **摘要**：ETL (Extract, Transform, Load) tools such as IBM DataStage allow users to visually assemble complex data workflows, but configuring stages and their properties remains time consuming and requires deep tool knowledge. We propose a system that translates natural language descriptio...

• 链接：https://arxiv.org/abs/2510.12825

        <div style="margin-top: 2rem; padding: 1rem; border-left: 3px solid #4a90d9; font-size: 0.9rem; opacity: 0.85;">
        完整深度阅读见博客文章，使用结构化三元组方法拆解论文逻辑。
        </div>
  

2. SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads

        - **来源**：deepxiv
        - **分数**：0.3644
        - **入选原因**：5 citations
        - **摘要**：Database research and development often require a large number of SQL queries for benchmarking purposes. However, acquiring real-world SQL queries is challenging due to privacy concerns, and existing SQL generation methods are limited in customization and in satisfying realistic ...

• 链接：https://arxiv.org/abs/2507.06192

        <div style="margin-top: 2rem; padding: 1rem; border-left: 3px solid #4a90d9; font-size: 0.9rem; opacity: 0.85;">
        完整深度阅读见博客文章，使用结构化三元组方法拆解论文逻辑。
        </div>
  

3. QUIS: Question-guided Insights Generation for Automated Exploratory Data Analysis

        - **来源**：deepxiv
        - **分数**：0.3344
        - **入选原因**：topic keywords matched; 2 citations
        - **摘要**：Discovering meaningful insights from a large dataset, known as Exploratory Data Analysis (EDA), is a challenging task that requires thorough exploration and analysis of the data. Automated Data Exploration (ADE) systems use goal-oriented methods with Large Language Models and Rei...

• 链接：https://arxiv.org/abs/2410.10270

        <div style="margin-top: 2rem; padding: 1rem; border-left: 3px solid #4a90d9; font-size: 0.9rem; opacity: 0.85;">
        完整深度阅读见博客文章，使用结构化三元组方法拆解论文逻辑。
        </div>
  

4. OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System

        - **来源**：deepxiv
        - **分数**：0.3332
        - **入选原因**：topic keywords matched; code signal; 16 citations; appeared 2x before
        - **摘要**：We introduce OneKE, a dockerized schema-guided knowledge extraction system, which can extract knowledge from the Web and raw PDF Books, and support various domains (science, news, etc.). Specifically, we design OneKE with multiple agents and a configure knowledge base. Different ...

• 链接：https://arxiv.org/abs/2412.20005

        <div style="margin-top: 2rem; padding: 1rem; border-left: 3px solid #4a90d9; font-size: 0.9rem; opacity: 0.85;">
        完整深度阅读见博客文章，使用结构化三元组方法拆解论文逻辑。
        </div>
  

5. IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpus

        - **来源**：deepxiv
        - **分数**：0.3325
        - **入选原因**：code signal; 19 citations; appeared 1x before
        - **摘要**：Large Language Models (LLMs) demonstrate remarkable potential across various domains; however, they exhibit a significant performance gap in Information Extraction (IE). Note that high-quality instruction data is the vital key for enhancing the specific capabilities of LLMs, whil...

• 链接：https://arxiv.org/abs/2402.14710

        <div style="margin-top: 2rem; padding: 1rem; border-left: 3px solid #4a90d9; font-size: 0.9rem; opacity: 0.85;">
        完整深度阅读见博客文章，使用结构化三元组方法拆解论文逻辑。
        </div>