AI Filtering Method for Literature Review

Introduction

• Discuss the challenge of managing a large collection of papers.
• Emphasize the goal of prioritizing reading and understanding relevant literature.

Using Li Maps and Citations

• Li Maps can be useful for assessing citations.
• Caution about trusting citations: high citations do not always equate to relevance.
• Importance of the order of reading and learning goals.

Goal-Oriented Reading List

• Define a learning goal: e.g., "Learn how to remove class noise from my dataset."
• Utilize ChatGPT to generate a reading list based on abstracts from a CSV file.

Prompting ChatGPT

• Provide ChatGPT with abstracts and ask it to create a progressive reading list.
• Goal: Start from broader concepts and advance to specific papers.
• Instruct ChatGPT to identify two questions per paper based on abstracts to clarify learning objectives.

Example Process

• Attempt to upload a CSV file of papers, including authors and abstracts.
• Initial attempts to generate a reading list may be inconsistent.
• Highlight the need for clear instructions to avoid missing relevant papers.

Limitations of AI

• AI may exclude papers and could produce varying results with repeated prompts.
• Caution advised when relying solely on AI-generated lists; ensure thoroughness.

Curated Reading List Approach

• Define relevance and importance for each paper read.
• Maintain clear goals to enhance memory and importance of selected papers.
• Example: Use a software system for organizing the reading list.

Original Literature Review Process

• Discuss the "detective mindset" for reading and analyzing papers.
• Identify key arguments and contrasting opinions within the literature on specific topics.

Conclusion

• AI tools can assist in creating curated reading lists efficiently.
• Manual engagement with literature remains valuable and necessary.
• Flexibility in approach: balance between AI assistance and traditional methods.