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Top-cited on a topic
A preconfigured run of Semantic Scholar Scraper — Papers & Citations: Top-cited on a topic. Input — mode: paper-search · query: large language models · sort: citationCount:desc · year: 2020-2024 · maxResults: 100. Results are returned as JSON rows in the default dataset; run it as-is or change the input and run your own.
Semantic Scholar Scraper — Papers & Citationsponderable_hydrometer/semantic-scholar-scraper
Type
Paper Id
Title
Year
+8 fieldsTextNumberBooleanListObject
Input
Mode:paper-search
Query (search modes):large language models
Sort (paper-search):citationCount:desc
Year filter (paper-search):2020-2024
Max results:100
Output fields
Type
Paper Id
Title
Year
Publication Date
Venue
Authors
Citation Count
Influential Citation Count
Reference Count
Doi
Arxiv Id
Sign up on Apify01
Create your Apify account to access the Semantic Scholar Scraper — Papers & Citations.
Start the run02
The Actor will start running based on the input automatically.
Receive the output03
Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.
Integrate into your workflow04
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.
