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Found 4 papers, 3 papers with code
SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification
Our evaluation shows that SpecInfer outperforms existing LLM serving systems by 1. 5-2. 8x for distributed LLM inference and by 2. 6-3. 5x for offloading-based LLM inference, while preserving the same generative performance.
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks
However, the search space for a mixed-precision quantization is exponential in the number of layers.
Unsupervised Projection Networks for Generative Adversarial Networks
We propose the use of unsupervised learning to train projection networks that project onto the latent space of an already trained generator.
Large batch size training of neural networks with adversarial training and second-order information
Our method exceeds the performance of existing solutions in terms of both accuracy and the number of SGD iterations (up to 1\% and $5\times$, respectively).
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