TEXAS: Task-Expert-Aware Supervision for Downstream Mixture-of-Experts LLM Adaptation
This work introduces Task-Expert-Aware Supervision (TEXAS), which combines correctness-conditioned task expert discovery with token-level supervision allocation and leverages existing routing behavior without restricting adaptation to a fixed expert subset or imposing an explicit target routing distribution.