External pipelines · RISE project catalogue
STORM / Co-STORM
An LLM-powered knowledge-curation system that writes Wikipedia-style long-form articles from web search. STORM uses perspective-guided question asking and simulated conversations between a writer and a topic expert; Co-STORM (EMNLP 2024) adds a collaborative discourse protocol with human-in-the-loop and a dynamic mind map.
Where it sits
left: what it builds on · right: what builds on it · pale: exampleContributed by Stanford OVAL
How studies reach it
No published study reaches it yet.
Disciplines it reaches
No study reaches it yet.
Solid: published studies. Light: examples.
Computed from the records on this site: what each study, template and specialist names as used, which study extends which, and who contributed what. 0 studies in total.
What it does
Treats the *pre-writing* problem (deciding what questions to ask) as the central bottleneck of automated long-form writing, and operationalizes it via perspective discovery and simulated expert dialogue. Co-STORM further makes the human–LLM curation loop a first-class architectural element.
- Focus
- literature
- Inputs
- topic
- Outputs
- long-form-article, citations, mind-map
- Architecture
- multi-agent, human-in-loop, tool-use, rag-knowledge-base, iterative-loop
- Maintained by
- Stanford OVAL
- Started
- 2024
Description
Data model- Discipline
- General
- Method family
- Literature review
- Design
- not specified
- Research stage
- Literature discoveryLiterature synthesisDrafting
- Contributors
- Stanford OVAL
- Usage
- not used in published research yet
- Source
- RISE project catalogue · projects/landscape · @4c17bae
- Record
- pipeline:storm · JSON
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Bring it into the standard
A pipeline built outside E2ER can meet the standard by describing its steps as a template, attaching the floor of checks and publishing evaluation records. Its authors keep ownership and credit.