jevPOST
用 Jev 做 agent 每步推理强度的路由控制
受 Ares 论文启发,作者认为 Jev 比微调小模型更适合在 agent 每步前决定推理力度,因为路由开销几乎不可见。
vechen
@miu215902026.09.22收录原推发布于 2026.09.22
vechen @miu21590原推发布于 2026.09.22
Inspired by Ares paper (https://arxiv.org/abs/2603.07915), which used a fine-tuned Qwen3-1.7B to pick reasoning effort before every agent step. Same idea, but Jev is a much better fit for this control loop: fast enough that the routing overhead is basically invisible. It’s especially practical now that Astra and the latest Claude models can change effort mid-conversation without invalidating the prompt cache.
x.com/miu21590/status/2102088570051658145采集于 2026.09.22 10:13