PQCache: Product Quantization-based KVCache for Long Context LLM Inference
Summary: PQCache uses PQ to compress KVCache for long-context LLM inference, treating KVCache as embedding retrieval. During prefilling and autoregressive decoding, PQ codes and centroids approximate key selection to fetch K/V, reducing overhead. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hailin Zhang (Peking University)
- 2. Xiaodong Ji (Peking University)
- 3. Yilin Chen (Peking University)
- 4. Fangcheng Fu (Peking University)
- 5. Xupeng Miao (Purdue University)
- 6. Xiaonan Nie (Peking University)
- 7. Weipeng Chen (Baichuan Inc.)
- 8. Bin Cui (Peking University)
BibTeX Citation
@inproceedings{zhang_sigmod25,
title = {{PQCache: Product Quantization-based KVCache for Long Context LLM Inference}},
author = {Zhang, Hailin and Ji, Xiaodong and Chen, Yilin and Fu, Fangcheng and Miao, Xupeng and Nie, Xiaonan and Chen, Weipeng and Cui, Bin},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725338},
url = {https://dl.acm.org/doi/10.1145/3725338},
year = {2025}
}
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