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Found 3 papers, 2 papers with code
SnapKV: LLM Knows What You are Looking for Before Generation
Specifically, SnapKV achieves a consistent decoding speed with a 3. 6x increase in generation speed and an 8. 2x enhancement in memory efficiency compared to baseline when processing inputs of 16K tokens.
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning
The Mixture of Experts (MoE) is a widely known neural architecture where an ensemble of specialized sub-models optimizes overall performance with a constant computational cost.
Exploring Low Rank Training of Deep Neural Networks
Training deep neural networks in low rank, i. e. with factorised layers, is of particular interest to the community: it offers efficiency over unfactorised training in terms of both memory consumption and training time.
