Paperlayer vs Scholarcy

Paperlayer is a web-based AI reading layer for research papers, pairing summaries and contextual margin notes with evidence in the original PDF. You can find public arXiv papers by title or author, enter an arXiv ID or paste an arXiv link. Summaries cover the paper’s problem, method, results and caveats, while highlights mark claims, methods, results, problems and caveats with adjustable density. Margin notes explain terms, equations and figures beside the text. Summaries and notes support Korean, Japanese, Chinese, Spanish, French and German, and J and K keys navigate through a paper. Paper chat is marked “Soon.” The public demo covers public arXiv papers only and accepts no private or unpublished uploads. Paperlayer says live processing sends paper and request content to OpenAI over encryption without intentionally including account, cookie or anonymous identifiers.

Scholarcy turns research material into interactive summary flashcards that highlight key information and provide context. It accepts research papers, PDFs, book chapters, online articles, plain text and YouTube videos. Users can add content by uploading or dropping files, entering a webpage URL, pasting text or using a browser extension. Enhanced summaries can be tailored to reading styles such as School level, General reader, Bulleted list, Undergrad level, One liner and Researcher. Research tools include cited-work findings, article prompts and questions, a Research Quality Indicator and comparisons with related research. Scholarcy imports directly from Zotero and exports referenced summaries to Markdown for tools including Roam, Obsidian and Notion. Extensions are offered for Chrome, Edge and Firefox; Safari is listed as coming soon. The free plan costs nothing and allows 10 summaries, with flashcards exported one at a time. Scanned PDFs without extractable text are unsupported unless OCR is run first, and URLs behind paywalls may not import. Scholarcy says customer data is encrypted at rest and in transit.