1 citations · 1 across the 16 of their papers we have counts for
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P2Flow: Phoneme-aware Progressive Flow Matching for Extreme Speech Super-Resolution
Ningyuan Yang, Yize Li, Pu Zhao +5
Generative models have recently demonstrated considerable promise in speech super-resolution (SSR). Nevertheless, the majority of existing work has concentrated on standard or vers…
MRMAD: A Multi-Round Multi-Audio Benchmark for Evaluating Acoustic Degradation Perception in Large Audio-Language Models
Yize Li, Ningyuan Yang, Sile Yin +6
Large audio-language models (LALMs) have shown promising progress in understanding speech, music, and general sound events, yet their ability to reason about how audio signals are…
A Survey of Advancing Audio Super-Resolution and Bandwidth Extension from Discriminative to Generative Models
Ningyuan Yang, Yize Li, Diego A. Cuji +4
Audio super-resolution (SR), also referred to as bandwidth extension (BWE), aims to reconstruct high-fidelity signals from low-resolution (LR) or band-limited (BL) observations, an…
HIERAMP: Coarse-to-Fine Autoregressive Amplification for Generative Dataset Distillation
Lin Zhao, Xinru Jiang, Xi Xiao +7
Dataset distillation often prioritizes global semantic proximity when creating small surrogate datasets for original large-scale ones. However, object semantics are inherently hier…
When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making
Jun Liu, Pu Zhao, Zhenglun Kong +12
Embodied robotic systems increasingly rely on large language model (LLM)-based agents to support high-level reasoning, planning, and decision-making during interactions with the en…