
Fanqing
@FanqingMengAI • 2,511 subscribers
Co-founder of @Evolvent_AI, Previous: @Kimi_Moonshot (focus on rl infra) , Now focus on agentic benchmark & infra, contact: [email protected]
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💡Our view: RSI is a systems engineering problem, not just a model problem. Progress depends on the environment a research agent works in: what resources it can call, what it can change, and how it runs experiments. That environment should reflect real production workflows and be easy for agents to use. At Evolvent AI, we built RSIGym around Everything as a Service. Agents can call established research services and iterate on data, training settings, and harness code. We also introduce RSI-Index to measure how well frontier agents jointly improve a target model’s weights and harness. Across 6 research agents and 5 benchmarks, Opus 5 leads at 0.4809. 🧵 We’re releasing the code, experiment configurations, research trajectories, and evaluation logs. Try your own improvement methods with RSIGym. 🌐 Website: 💻 GitHub: 📄 arXiv:
Fanqing381,851 Aufrufe • vor 24 Tagen
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