Academic & Research

Scrape Google Scholar Papers and Citations

Turn academic search into structured research data

Discover literature, track citation networks, or benchmark research output. Extract papers, citations, publication metadata, and abstracts ready for analysis.

How it works

  1. 1 Enter your search query or URL in the form
  2. 2 Click search and we'll extract the data in seconds
  3. 3 View results online or download as CSV
Cost: 2 credits per row
Format: CSV download

400 credits · $0.80

$1.00 min. purchase — unused credits stay in your account

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Tool Google Scholar
Rows 20
Report cost 50 credits
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No credit card required Results in seconds CSV download 2 credits per row

What You Get

We extract structured data from the source and deliver it as a clean, downloadable CSV.

scholar.google.com/scholar?q=transformer architecture deep learning
[PDF]

Attention Is All You Need

A Vaswani, N Shazeer, et al. - NeurIPS, 2017

We propose a new simple network architecture, the Transformer, based solely on attention mechanisms...

★ Save ❝ Cite Cited by 124500 Related
[BOOK]

BERT: Pre-training of Deep Bidirectional Transformers

J Devlin, MW Chang, et al. - NAACL, 2019

We introduce BERT, a new language representation model designed to pre-train deep bidirectional...

★ Save ❝ Cite Cited by 89200 Related

An Image is Worth 16x16 Words: Transformers for Image Recognition

A Dosovitskiy, L Beyer, et al. - ICLR, 2021

We show that a pure transformer applied directly to sequences of image patches can perform...

★ Save ❝ Cite Cited by 34800 Related

Source page

Structured CSV
Position
Title
Link
1
Attention Is All You Need
https://arxiv.org/abs/1706.03762
2
BERT: Pre-training of Deep Bidirectional Transformers
https://arxiv.org/abs/1810.04805
3
An Image is Worth 16x16 Words: Transformers for Image Recognition
https://arxiv.org/abs/2010.11929

Clean, downloadable data

Complete Data Preview

Here's every field you'll get when you run Google Scholar.

Example search:transformer architecture deep learning
Position Title Link Snippet Publication Info Cited By Count Year Resources
1 Attention Is All You Need https://arxiv.org/abs/1706.03762 We propose a new simple network architecture, the Transformer, based solely on attention mechanisms... A Vaswani, N Shazeer, et al. - NeurIPS, 2017 124500 2017 [PDF] arxiv.org
2 BERT: Pre-training of Deep Bidirectional Transformers https://arxiv.org/abs/1810.04805 We introduce BERT, a new language representation model designed to pre-train deep bidirectional... J Devlin, MW Chang, et al. - NAACL, 2019 89200 2019 [PDF] arxiv.org
3 An Image is Worth 16x16 Words: Transformers for Image Recognition https://arxiv.org/abs/2010.11929 We show that a pure transformer applied directly to sequences of image patches can perform... A Dosovitskiy, L Beyer, et al. - ICLR, 2021 34800 2021 [PDF] openreview.net
Sample data for illustration

Why ScrapeBase?

Skip the complexity. Get the data.

Feature DIY / Raw APIs
ScrapeBase Recommended
Setup time
Hours to days
Minutes
Code required
Yes — scripts to maintain
None
Proxies & CAPTCHAs
You handle it
We handle it
Rate limits & retries
You build it
Automatic
Infrastructure
Your servers & keys
Nothing to manage
Data output
Raw — needs parsing
Clean CSV

What You Can Do

Automate Literature Reviews

Scrape Google Scholar results for any research topic to build comprehensive literature databases with citation counts and links.

Track Research Trends

Monitor which papers and topics gain traction in academia by tracking citation velocity and publication frequency over time.

Build Academic Datasets

Extract structured data from thousands of scholarly articles — titles, authors, journals, dates, and citation counts — at scale.

Built for Speed and Reliability

Average response time under 10 seconds

Structured, clean data ready for analysis

CSV export, spreadsheet-ready

Reliable infrastructure, always available

Frequently Asked Questions

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