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RUC-NLPIR/Arbor

Arbor RUC-NLPIR/Arbor is an Apache-2.0 generalist autonomous research agent that turns a long-horizon objective into a cumulative search by proposing hypotheses, editing code, running real experiments, learning from the results, and keeping the improvements that hold up on held-out data, replaces one-shot attempts that forget what failed with a hypothesis tree where every idea becomes a branch — p

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Score8.2
Popularity657.0
Risklow
TierGold
Score breakdown
Usefulness8.6
Novelty10.0
Momentum10.0
Maturity8.9
Open-source/build7.4
Evidence7.2
Workflow potential9.3
Setup ease6.5

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Why it matters

Useful for ML researchers, research engineers, agent developers, AI engineers, applied scientists, grad students, eval teams, prompt engineers, harness engineers, and any operator running long-horizon agent optimization where one-shot attempts forget what failed and insight-propagation matters more than raw throughput, because RUC-NLPIR/Arbor is an Apache-2.0 generalist autonomous research agent t

Who should use it

BuildersPower users

Who should skip it

Skip if the source link, docs, or setup requirements do not match your workflow.

Risk explanation

Risk label needs manual review.

Evidence links

Closest alternatives / related signals

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