Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling 事件

Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling arXiv:2606.03102v1 Announce Type: new Abstract: Test-time scaling improves the reasoning performance of large language models but incurs substantial cost in both total computation and latency. Existing adaptive sampling methods partially mitigate this issue by dynamically deciding when to stop sampling, yet they typically rely on heuristic rules or rely on distribution assumptions. In this work, we form