Papers by Dongping Liao

1 papers
Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization (2025.emnlp-main)

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Challenge: Existing methods for token-level KV optimization and grouping of tokens are inefficient and strain compute and storage resources.
Approach: They propose a mixture-of-expert approach that dynamically optimizes token-wise computation and memory allocation by a token-based expert-choice routing mechanism guided by learned importance scores.
Outcome: The proposed approach retains all tokens while adaptively routing them to specialized experts with varying KV group sizes, balancing granularity and efficiency.

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