Search Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, and novel research hypotheses.

For novel ML/AI research ideas, use search_type="hypothesis", then get_hypothesis on promising results.

search_type accepts all, cluster/direction, paper, author, institution, venue, or hypothesis/proposal; singular and plural aliases are accepted. Use other sources for biographies, news, and non-research web content.

ranking_profile accepts:

• default / lexical (default): production ranking; relevance-sorted paper searches combine lexical and semantic retrieval when fields is unset.

• semantic: conceptual paper retrieval; supported for paper and all.

• bm25_title_abstract / bm25: lexical paper matching over those fields.

sort accepts relevance (default), year_desc, or year_asc. Semantic ranking cannot use year sorting; constrain recency with date_from/date_to instead. date_from and date_to are inclusive YYYY, YYYY-MM, or YYYY-MM-DD bounds.

fields optionally restricts and weights lexical fields, for example "title^4,abstract". Supported names are title, abstract, summary, concepts, name, top_names, and venue. Fields must exist on the selected search_type, weights must be within 0 < weight <= 100, and fields cannot be combined with semantic ranking.

Fetch a generated novel ML/AI research proposal from Lacuna.

Use after search_lacuna(search_type="hypothesis") to inspect a proposal.

view selects the response shape:

• "context" (default, recommended): compact single-fetch proposal context — summary_markdown, abstract, and linked directions, with the raw upstream record (whose markdown duplicates summary_markdown) dropped server-side.

• "full": the server's version record, including version history and signal counts. Proposal bodies are in versions[].markdown. Use only when you need versions or signals.

Fetch a Lacuna research direction/cluster.

view selects the response shape (context typically contains the fields full provides plus the agent-oriented summary content):

• "context" (default, recommended): compact agent-oriented summary with summary_markdown, capped papers/authors/related_directions, and truncation markers.

• "full": raw upstream cluster record only. Cheaper than context when you only need basic cluster metadata.

Fetch paginated papers associated with a Lacuna research direction/cluster.

view selects the per-paper shape:

• "compact" (default, recommended): citation-ready rows (id, url, title, year, venue, a few authors, abstract snippet). Drops the raw upstream info blob and levels.cluster internals that otherwise dominate the payload.

• "full": the complete upstream paper records. Much larger; use only when you need the raw metadata (openalex/dblp/arxiv ids, etc.).

Fetch a Lacuna paper by artifact id or paper URL.

view selects the response shape. context requests Lacuna's compact agent-oriented context by default, while the four single-field views (blog/figures/concepts/neighbors) return isolated sub-resources:

• "context" (default, recommended): agent-oriented summary with summary_markdown, authors, and a small figure preview. Start here for almost everything.

• "full": raw upstream paper record only. Cheaper than context when you only need basic metadata.

• "preview": compact card with unique fields excerpt, excerpt_kind, bookmarked. Use for citation-style display.

• "blog": just the summary_markdown content, without the rest of the context envelope.

• "figures": just the figures list.

• "concepts": just the concepts list.

• "neighbors": just the related-papers list.

figure_limit (context view only) caps the figure preview (server default 3). Pass 0 to suppress figure previews while keeping a figures_truncated signal.

Fetch one page of an author's papers, ordered from newest to oldest.

Fetch one page of an author's named research directions.

Fetch agent-oriented context for a Lacuna author.

Author profiles describe research output (papers, directions, impact). A free-text affiliation field may be present but can be incomplete or outdated and may not represent current employment; the corpus has no biography or employment history, so do not infer those from this data.

view selects the response shape:

• "context" (default, recommended): Lacuna's compact author context — capped readable papers and an impact_directions list (named research directions) in place of the raw numeric impact_clusters telemetry, with the duplicated nested author record dropped server-side.

• "full": the bounded full-shape author context (raw impact_clusters, nested author record; server collections are capped at 100).

Set include_neighbors=True to include similar authors as named, linkable records. Neighbor computation may add significant server latency.

Fetch one ranked page of neighboring/similar Lacuna authors.

Fetch agent-oriented context for a Lacuna venue, optionally scoped to a year.

Venue keys are opaque hashes (e.g. "d7bf22905bd6"), never human-readable names like "icml". Find the key first via search_lacuna(search_type="venue") or pass a /venue/... page URL.

view selects the response shape:

• "context" (default, recommended): compact venue context — capped top authors, non-placeholder top clusters, and a recent-activity slice (the requested year is always included), with the duplicated venue block and full year histogram dropped server-side.

• "full": the complete venue context (full year histogram, all top authors/ clusters, duplicated venue record).

Fetch agent-oriented context for a Lacuna institution.

view selects the response shape:

• "context" (default, recommended): compact institution context — capped top authors with the duplicated institution block dropped server-side.

• "full": the complete institution context shape (duplicated institution record and a bounded author list with explicit truncation metadata).

Use get_institution_authors to page through the complete author list.

Fetch one page of authors affiliated with a Lacuna institution.

Results are ordered by paper count. Use authors_total, authors_returned, authors_offset, and authors_truncated to page through the complete list.