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Serving Deep Learning Model in Relational Databases

Published in Proceedings of the International Conference on Extending Database Technology (EDBT), 2024

We propose a method for serving deep learning models within relational database systems.

Recommended citation: Lixi Zhou*, Qi Lin*, Jia Zou. "Serving Deep Learning Model in Relational Databases." Proceedings of the International Conference on Extending Database Technology (EDBT), 2024.

RollStore: Hybrid Data Indexing for Decentralized Blockchain Applications

Published in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024

We present RollStore, a hybrid data indexing approach for decentralized blockchain applications.

Recommended citation: Qi Lin, Binbin Gu, Faisal Nawab. "RollStore: Hybrid Data Indexing for Decentralized Blockchain Applications." IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.

Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework

Published in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025

A comprehensive analysis and defense framework for bit-flip error resilience in large language models.

Recommended citation: Yuhang Chen, Zhen Tan, Ajay Kumar Jaiswal, Huaizhi Qu, Xinyu Zhao, Qi Lin, Yu Cheng, Andrew Kwong, Zhichao Cao, Tianlong Chen. "Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework." Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.

O3-LSM: Maximizing Disaggregated LSM Write Performance via Three-Layer Offloading

Published in Proceedings of ACM Conference on Management of Data (SIGMOD), 2026

We design an LSM-based KV store leveraging Disaggregated Memory via RDMA to scale writes, achieving 4.5x higher write throughput and 76% lower P99 latency.

Recommended citation: Qi Lin, Gangqi Huang, Te Guo, Chang Guo, Viraj Thakkar, Zichen Zhu, Jianguo Wang, Zhichao Cao. "O3-LSM: Maximizing Disaggregated LSM Write Performance via Three-Layer Offloading." Proceedings of ACM Conference on Management of Data (SIGMOD), 2026.