Author used ChatGPT to summarize and structure a thesis literature review, and tried a tool that builds summaries from real papers to avoid invented citations.
Author used ChatGPT to summarize and structure a thesis literature review, and tried a tool that builds summaries from real papers to avoid invented citations.
The poster used ChatGPT for two parts of an early thesis literature review: summarizing papers and helping structure the review. After finding that ChatGPT sometimes produced convincing but nonexistent or misread references, they started trying Literfy AI instead because it pulls real academic papers first and then builds summaries from those sources.
The source gives no hard performance numbers. The reported result was mainly less mental strain and more confidence that cited sources were real, though the poster said it was still early and did not claim full trust in AI.
Their main catch was citation reliability: they still had to verify sources because ChatGPT had generated realistic-looking references that did not exist.
I am writing a literature review for my thesis on [topic]. Find real papers on [subtopics], summarize each in 3 to 4 sentences, group them into themes, and propose a structure for the review. Give a link or DOI for every source and mark anything you could not verify, so I can check each citation before using it.
Export the Descript transcript, let ChatGPT pick the five strongest moments, and get 10 platform-ready posts in a review doc within minutes.
Give it a keyword and get a brief built from the pages that rank today: headings, gaps, questions to answer and a target length.
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