Papers by Yuhang Lou

1 papers
From Outcome to Process: Optimizing MoE Load Balancing with MCTS (2026.findings-acl)

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Challenge: Existing balancing strategies focus on constraining the final distribution of expert usage, but overlook the routing decisions made at each layer.
Approach: They propose a three-stage framework that leverages process-level rewards to guide balanced expert routing.
Outcome: Extensive experiments show that LayerMoE improves the performance of state-of-the-art LoRA-MoA baselines, yielding an average accuracy gain of 1.39%.

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