Papers with similarity of neural network algorithm

1 papers
SimSMoE: Toward Efficient Training Mixture of Experts via Solving Representational Collapse (2025.findings-naacl)

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Challenge: Sparse mixture of experts (SMoE) is an effective approach for scaling large language models with a constant computational cost.
Approach: They propose a similarity-based sparse mixture of experts (SimSMoE) that guarantees a solution to address the representation collapse problem between experts given a fixed FLOPs budget.
Outcome: The proposed method outperforms existing methods and outperformed other SMoE routing methods in performance.

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