Relevance-ranked plain-text search over 200M+ papers, with year,
field-of-study, publication-type, open-access, and citation-count filters.
The query is sent unchanged; boolean and quoted-phrase syntax is
documented only for semantic_scholar_bulk_search. Page with
offset/limit (max 100 per call). For sorted or very large result sets
use semantic_scholar_bulk_search; to search inside paper full text use
semantic_scholar_snippet_search; to resolve one known title use
semantic_scholar_match_paper. Returns Markdown by default,
response_format='json' for raw JSON.

Returns title, abstract, authors, venue, year, citation counts, TLDR,
and open-access PDF link for one paper, e.g. paper_id='ARXIV:1706.03762'.
Set include_citations / include_references to also list citing and
referenced papers (fetched in parallel, 1-100 per page each). Paginate
the two directions independently with citations_offset/references_offset;
JSON output exposes citations_page.next and references_page.next.
Results are cached
in memory for 5 minutes; an unknown ID raises a not-found error. Client-side
requests use a 1.0-second unkeyed interval and a conservative 1.1-second
authenticated default; explicitly higher S2-assigned quotas can be configured.
429/502/503 responses retry automatically with backoff. Returns
Markdown by default, response_format='json' for raw JSON. To fetch many
papers at once use semantic_scholar_bulk_papers.

Example: query='Yoshua Bengio'. Several distinct researchers can share a
name, so confirm identity with semantic_scholar_get_author (affiliations,
h-index, publications) before attributing work; to list the authors of a
specific paper use semantic_scholar_paper_authors instead. Page with
offset/limit (max 100 per call, default 10). Returns Markdown by default,
response_format='json' for raw JSON.

Provide one paper you already know (e.g. paper_id='ARXIV:1706.03762') and
receive up to `limit` similar papers. from_pool picks the candidate pool:
'recent' (default, recently published papers from all fields) or 'all-cs'
(computer-science papers of any age). When steering with several positive
or negative examples, use semantic_scholar_multi_recommend instead. An
unknown seed ID raises a not-found error. Client-side requests use a
1.0-second unkeyed interval and a conservative 1.1-second authenticated
default; explicitly higher S2-assigned quotas can be configured. 429/502/503
responses retry automatically with backoff. Returns Markdown by default,
response_format='json' for raw JSON.

Unlike regular search, supports sorting (e.g., by citation count), boolean
query syntax, and returns a continuation token for paging through all
results. The observed endpoint ignores ``limit`` and may return up to 1000
papers per page; the full page is returned so no row is skipped.

Use once you have a paper ID (from semantic_scholar_search_papers or
semantic_scholar_match_paper), e.g. paper_id='DOI:10.18653/v1/N18-3011'.
Returns the BibTeX entry as plain text - there is no response_format
option. Raises an error for an unknown ID, a paper without citation data,
or any format other than 'bibtex'.

Unlike the abbreviated author list embedded in semantic_scholar_get_paper
results, this returns each author's complete profile - affiliations,
h-index, paper and citation counts - plus author IDs usable with
semantic_scholar_get_author. Example: paper_id='DOI:10.18653/v1/N18-3011'.
Authors are returned in listed order (limit 1-1000, default 100). Returns
Markdown by default, response_format='json' for raw JSON.

Use instead of semantic_scholar_recommendations when steering with more
than one example: results resemble positive_paper_ids and are pushed away
from negative_paper_ids. Example:
positive_paper_ids=['ARXIV:1706.03762', 'DOI:10.18653/v1/N19-1423'],
negative_paper_ids=['ARXIV:1409.0473']. Accepts 1-100 positive and up to
100 negative IDs in any supported paper-ID format; malformed IDs raise an
error before any request is made. Returns up to `limit` (1-500, default
10) papers, Markdown by default or response_format='json' for raw JSON.

Note: This endpoint is heavily rate-limited without an API key.