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Data Engineering and Feature Optimization

Applications of LLMs in data processing, feature engineering, and tabular data optimization

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Data Engineering and Feature Optimization

Research on Large Language Models in Data Engineering and Feature Optimization

Automating Feature Engineering with AI

Automating Feature Engineering with AI

Using LLMs to Generate Intelligent Features for Tabular Data

Breaking SQL Dialect Barriers

Breaking SQL Dialect Barriers

A Hybrid Approach to Translate SQL Across Database Systems

Turbocharging Database Recursion

Turbocharging Database Recursion

A Type-Safe Approach to Recursive Queries with Superior Performance

AI-Powered ELT Pipeline Automation

AI-Powered ELT Pipeline Automation

First end-to-end benchmark for evaluating AI agents on data pipelines

LEMUR: Enabling Next-Gen AutoML

LEMUR: Enabling Next-Gen AutoML

A comprehensive neural network dataset for seamless AI development

Universal Graph Encoding Breakthrough

Universal Graph Encoding Breakthrough

Transforming structural information across graph domains

Enterprise LLMs: Beyond the Hype

Enterprise LLMs: Beyond the Hype

Addressing unique challenges for LLMs in data engineering workflows

Rethinking Retrieval Systems

Rethinking Retrieval Systems

Beyond Cascading: A New Approach to Multi-Model Retrieval

Key Takeaways

Summary of Research on Data Engineering and Feature Optimization

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