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Xiangsheng Shi

2 accepted papers

2024

Evaluating Quantized Large Language Models

ICML 2024poster

Post-training quantization (PTQ) has emerged as a promising technique to reduce the cost of large language models (LLMs). Specifically, PTQ can effectively mitigate memory consumption and reduce computational overhead in LLMs. To meet the requirements of both high efficiency and performance across d…

2023

Memory-Oriented Structural Pruning for Efficient Image Restoration

AAAI 2023technical

Deep learning (DL) based methods have significantly pushed forward the state-of-the-art for image restoration (IR) task. Nevertheless, DL-based IR models are highly computation- and memory-intensive. The surging demands for processing higher-resolution images and multi-task paralleling in practical…

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