Tools
6/ When RL Meets Adaptive Speculative Training: A Unified Training-Serving System (Aurora) Paper: https://arxiv.org/abs/2602.06932
Aurora is a unified training-serving system that integrates reinforcement learning with adaptive speculative training to optimize large language model inference and training efficiency. The system dyn
Aurora is a unified training-serving system that integrates reinforcement learning with adaptive speculative training to optimize large language model inference and training efficiency. The system dynamically adjusts speculation strategies during both training and serving phases to improve throughput while maintaining model quality. This approach enables more efficient resource utilization by combining RL-driven optimization with speculative decoding techniques.
Source: Together AI (X) | 2026-07-01