multi-environment

The paper introduces Dyad, an architecture that augments LLMs with an environment-conditioned action encoder for native typed decision-making, showing that training the encoder alone enables modular adaptation and joint training outperforms conventional RL post-training, including a 3.80% gain on ALFWorld with a 9B model.