EdgeBench: Scaling Laws for Learning in Real-World Environments
ByteDance-Seed · hf · 2026-07-07
ByteDance's Seed team analyzed approximately 38,000 hours of real-world agent interaction data across 134 diverse tasks. They discovered that performance follows a log-sigmoid scaling law accompanied by an exponential increase in learning speed, revealing the scaling patterns of learning in real-world environments.
Related event: ByteDance Releases EdgeBench to Evaluate Long-Horizon Agent Evolution(4 posts)→
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