Shen Hu — accepted AI-conference papers

2026

AMR-LLM: Knowledge-Enhanced Multi-Modal Automatic Modulation Recognition via Large Language Models

Shen Hu, Yuhua Qian, Xinyan Liang, Zikun Jin, Jiaqian Zhang, Jiangfeng Zhang

IJCAI 2026

Existing multi-modal automatic modulation recognition (AMR) methods primarily focus on exploiting multi-view representations of raw signal data to improve performance, but still struggle to effectively model and exploit high-level human prior knowledge. Although recent studies attempt to introduce l

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2026

Signal Enhancement via Multi-view Dynamic Representation and Alignment-aware Fusion

Zikun Jin, Yuhua Qian, Xinyan Liang, Jiaqian Zhang, Jinpeng Yuan, Shen Hu +2

AAAI 2026technical

Robust signal enhancement under non-stationary and low SNR conditions remains challenging, as methods based on the short-time Fourier transform (STFT) with fixed resolution struggle to represent complex and time–frequency structures. While leveraging the fractional domain as an auxiliary view offers

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