NVIDIA 发布自进化代理框架 SoL-Pi，减少 50% 令牌流量
Build your own harness, folks. This is absolute banger paper from NVIDIA on self-evolving agent har...
NVIDIA 新方法能自动优化代理，减少 50% 令牌流量，比其他框架更省钱。
NVIDIA 新研究 SoL-Pi 通过自动优化代理执行机制，在 GPT-5.6 和 Opus 5 基准上匹配基线性能。在 51 任务 EdgeBench 测试中，其节省的 API 成本约为每小时 8.75 到 13.50 美元，比原生 Codex 和 Claude Code 框架节省约三分之一。
Build your own harness, folks. This is absolute banger paper from NVIDIA on self-evolving agent har...
Build your own harness, folks. This is absolute banger paper from NVIDIA on self-evolving agent harnesses. (bookmark it) They introduce SoL-Pi which cuts token traffic by nearly half. And it matches its baseline harness on GPT-5.6 Sol and Opus 5. More details below: Instead of tuning a harness by hand, they run auto-research loops at the harness layer across many repository-derived and verifier-driven environments, keeping only the mechanisms that survive selection. Four mechanisms survived: > Action Fusion changes how actions execute > Online Context Compact handles compaction during a run > ObservationPack reshapes observation handling > Evidence-Preserving Reducer covers delegated reading On the 51-task EdgeBench evaluation, the savings translate to about a third off API cost. In dollars that is an estimated $8.75 to $13.50 per hour against native Codex and Claude Code harnesses, and $4.36 to $5.71 against the baseline harness. Because the search runs across many environments rather than one, the retained mechanisms keep working outside the setting that produced them. Code is on GitHub under NVlabs. Paper: arxiv.org/abs/2609.20519 Chat with Paper: academy.dair.ai/papers/sol-pi-… 💬 18 🔄 26 ❤️ 273 👀 12768 📊 115 ⚡
