Papers by Xinyan Shi

1 papers
Efficient Learned Data Compression via Dual-Stream Feature Decoupling (2026.acl-long)

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Challenge: Learned data compression has achieved superior compression ratios, but balancing precise probability modeling with system efficiency remains challenging.
Approach: They propose a Dual-Stream Multi-Scale Decoupler that disentangles local and global contexts to replace deep serial processing with shallow parallel streams.
Outcome: The proposed method achieves state-of-the-art performance in both compression ratio and throughput while maintaining the lowest latency and memory usage.

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