External pipelines · RISE project catalogue
Scholar Loop
A single-maintainer "autonomous AI scientist" that runs the full PhD loop on a single-GPU budget: literature scouting (arXiv + OpenAlex, citation-ranked), grounded hypothesis generation, debate-gated real PyTorch experiments in a smoke -> verify -> full funnel, reflection into a time-decaying skill library, and a number-grounded write-up with self-review — all under a self-stopping budget governor. Sits with the AI-scientist family (Sakana, Agent Laboratory) but leads with deterministic anti-reward-hacking guards rather than scale.
Where it sits
left: what it builds on · right: what builds on it · pale: exampleContributed by renee-jia
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 outer loop and its integrity guards as the product: two-phase frozen scoring the experiment code cannot fake, an edit allowlist, a VerifiedRegistry that grounds every number in the draft, and universal predict-then-verify calibration that scores each agent's checkable claims against ground truth — with a bundled adversarial "cheater" engine to prove the guards hold, and the whole eight-agent loop testable deterministically without an API key or GPU.
- Focus
- end-to-end
- Inputs
- domain-profile, budget-config
- Outputs
- paper-draft, review-report, run-ledger, skill-library
- Architecture
- multi-agent, tool-use, iterative-loop, persistent-memory, debate-consensus
- Maintained by
- renee-jia
- Started
- 2026
Description
Data model- Discipline
- Computer science
- Method family
- not specified
- Design
- not specified
- Research stage
- Literature discoveryLiterature synthesisHypothesesCode generationData analysisDraftingReview
- Contributors
- renee-jia
- Usage
- not used in published research yet
- Source
- RISE project catalogue · projects/landscape · @4c17bae
- Record
- pipeline:scholar-loop · JSON
Solid tags are declared by the source or mapped from its terms; dashed tags are inferred by a published rule. Hover a tag for its provenance.
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.