Automatic highlights
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AI analyzes the full paper and marks key passages directly in the source.
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One paper, one workspace
Translate, ask questions, and take notes beside the source
No need to copy the paper or jump between different tools.
One paper, one workspace
No need to copy the paper or jump between different tools.
- Current paper · 15 pages
- Translation · 04 / 15
Complete paper reading
Everything you need to read a paper, right beside the source
Translate, explain, ask, and take notes without copying and pasting.
Page translation
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Translation appears beside each source page, so page numbers, formulas, and tables are easy to check.
- Follows original page numbers
- View source and translation side by side
Full-paper questions
Ask questions across the paper and trace every answer to its source
Follow up on methods, formulas, and conclusions, then jump from a source to the matching page.
- Answers use the full paper
- Jump back to the source
Selection explanations
Select a term, passage, or formula for an instant explanation
No copying and pasting. The explanation stays linked to the current page.
- No copy and paste
- Linked to the current page
Automatic highlights
Automatically highlight methods, novelty, and results
See the paper’s key passages first, then decide what deserves a closer read.
- Methods, novelty, and results
- Filter or delete highlights
Research notes
Highlights and notes stay where you left them
Record important points on the source and pick up where you left off next time.
- Records keep the source location
- Continue when you reopen
Figures and formulas
Select a figure or formula and ask
Understand trends, comparisons, and how they support the paper’s conclusions.
- Analyze in page context
- Verify on the original page
Full-paper questions
Ask questions across the paper and trace every answer to its source
Ask about methods, formulas, and experimental conclusions, then click through to the matching page.
Full paper · Page 4 selectionExplixit
Full-paper questionsWhy is multi-head attention necessary here?
Multi-head attention tracks dependencies across different representation subspaces, addressing the sequence-modeling limitation discussed earlier.
Back to source · Page 4Designed around the PDF
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