TIGER-AI-Lab/RewardHarness
Self-evolving agentic reward framework for image-editing evaluation — 47.4% on EditReward-Bench from only 100 preference demos, no reward-model training. arXiv 2605.08703.
19
Stars
7
Forks
32.5
Radar Score
Rising
Momentum
Scoring Breakdown
Impact9.1
Velocity42.2
Health56.6
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python
Why it ranks
Steady growth — consistently collecting stars and contributors.
Evaluation & Benchmarks · benchmarkTop 78% globally
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🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
NOASSERTION
Review license terms carefully before commercial adoption.
Health Grade
A
Based on maintenance, issue response, and release cadence.
Radar Score
32.5
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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