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Found 2 papers, 1 papers with code
Extreme Compression of Large Language Models via Additive Quantization
The emergence of accurate open large language models (LLMs) has led to a race towards quantization techniques for such models enabling execution on end-user devices.
Correlated Quantization for Faster Nonconvex Distributed Optimization
We analyze the forefront distributed non-convex optimization algorithm MARINA (Gorbunov et al., 2022) utilizing the proposed correlated quantizers and show that it outperforms the original MARINA and distributed SGD of Suresh et al. (2022) with regard to the communication complexity.
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