can-llms-clean-up-your-mess-a-survey-of-applicatio

name	can-llms-clean-up-your-mess-a-survey-of-applicatio
title	Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs
version	0.0.2
engine	skillxiv-v0.0.2-claude-opus-4.6
license	MIT
url	https://arxiv.org/abs/2601.17058
keywords	["research","methodology"]
description	Implement techniques from Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs. Data preparation aims to denoise raw datasets, uncover cross-dataset relationships, and extract valuable insights from them, which is essential for a wide range of data-centric applications

Overview

This skill implements concepts from the research paper [2601.17058].

When to Use

• When you need to implement techniques described in this paper
• When working on problems that this research addresses
• When you want to understand the core concepts and methodology

When NOT to Use

• This skill provides research-level insights; production implementations may require additional engineering
• Some concepts may require significant tuning for specific use cases
• Always evaluate applicability to your specific problem domain

Key Concepts

The paper addresses: Data preparation aims to denoise raw datasets, uncover cross-dataset relationships, and extract valuable insights from them, which is essential for a wide range of data-centric applications. Driven by (i) rising demands for application-ready data (e....

For detailed methodology, refer to the full paper.