Google Scholar Search#

Search academic papers using the free Semantic Scholar API. No API key required.

Quick Start#

Basic search:

bash

python3 {baseDir}/scripts/search_papers.py "machine learning transformers"

Search with filters:

bash

python3 {baseDir}/scripts/search_papers.py "deep learning" --limit 5 --year 2020-2023 --min-citations 10

Search Options#

• --limit N: Number of results (default: 10, max: 100)
• --year YYYY-YYYY: Filter by year range (e.g., "2020-2023" or "2023")
• --min-citations N: Minimum citation count
• --json: Output in JSON format for machine processing

Get Paper Details#

Retrieve detailed information about a specific paper:

bash

python3 {baseDir}/scripts/search_papers.py --details <paper-id>

Returned Data#

Each paper includes:

• title: Paper title
• authors: List of authors with names
• year: Publication year
• venue: Journal or conference name
• citationCount: Number of citations
• abstract: Paper abstract
• url: Link to Semantic Scholar page
• openAccessPdf: Direct PDF link if available
• paperId: Unique Semantic Scholar ID (for details lookup)

Examples#

Search for recent AI papers:

bash

python3 {baseDir}/scripts/search_papers.py "large language models" --year 2022-2024 --limit 10

Find highly cited papers on a topic:

bash

python3 {baseDir}/scripts/search_papers.py "quantum computing" --min-citations 50 --limit 10

Get JSON output for integration:

bash

python3 {baseDir}/scripts/search_papers.py "neural networks" --json --limit 20

Tips#

• Use specific keywords for better results
• Filter by year to get recent research
• Use --min-citations to find influential papers
• The API is free and requires no authentication
• For complex queries, try multiple related terms