Author

Yu-Dong Li

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Preprint Oct 2026

AuraSE: Low-Hallucination Generative Speech Enhancement via Multimodal Flow Matching and Inference Policy Optimization

Generative speech enhancement models can produce cleaner and more natural-sounding speech than conventional discriminative approaches, but may hallucinate by changing speech content or speaker identity, even with transcript conditioning. We present AuraSE, a flow-matching framework that addresses hallucination through...

Ying Shen, Yao Qian, Yuxuan Hu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Uncheatable Eval: Dynamic Compression-Based Evaluation of Language Models

This work uses compression rate to evaluate how well models predict new text, and results yield three main findings: compression performance follows a consistent scaling trend with model size, and lower compression rates are strongly associated with higher zero-shot MMLU accuracy.

Kai-Feng Tan, Yu-Dong Li, LinLin Shen · 0 citations