multi-teacher-distillation

Agents-A1 is a 35B Mixture-of-Experts agentic model from InternScience that achieves competitive performance against frontier-scale systems like GPT-5.5 and DeepSeek-V4-pro using long-horizon trajectory scaling and multi-teacher multi-domain distillation.

MOPD proposes a multi-teacher on-policy distillation paradigm for LLM post-training, enabling efficient integration of multiple domain capabilities by distilling specialized RL teachers into a student model using its own rollouts. It outperforms existing methods like Mix-RL and Cascade RL, and has been deployed in industrial-scale models.