LICO: An SIMD-Aware High-Performance Learned Inverted Index Compression Framework
Summary: LICO is an SIMD-aware learned inverted-index compressor using error-bounded models plus residuals for lossless decoding. It automatically adapts to distributions, provides theoretical compression guarantees, and achieves Pareto-optimal size/latency versus classical and learned schemes. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Xianyu Zhu (Renmin University of China)
- 2. Qiyu Liu (Southwest University)
- 3. Guangyi Zhang (Shenzhen University)
- 4. Zhibing Sha (Southwest University)
- 5. Jianwei Liao (Southwest University)
- 6. Sha Hu (Southwest University)
- 7. Lei Chen (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{zhu_sigmod26,
title = {{LICO: An SIMD-Aware High-Performance Learned Inverted Index Compression Framework}},
author = {Zhu, Xianyu and Liu, Qiyu and Zhang, Guangyi and Sha, Zhibing and Liao, Jianwei and Hu, Sha and Chen, Lei},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802079},
url = {https://dl.acm.org/doi/10.1145/3802079},
year = {2026}
}
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