1 citations · 1 across the 1 of their papers we have counts for
7 papers
Audio-Language Models for Audio-Centric Tasks: A Systematic Survey
Yi Su, Jisheng Bai, Qisheng Xu +2
Audio-Language Models (ALMs), trained on paired audio-text data, are designed to process, understand, and reason about audio-centric multimodal content. Unlike traditional supervis…
MAny: Merge Anything for Multimodal Continual Instruction Tuning
Zijian Gao, Wangwang Jia, Xingxing Zhang +6
Multimodal Continual Instruction Tuning (MCIT) is essential for sequential task adaptation of Multimodal Large Language Models (MLLMs) but is severely restricted by catastrophic fo…
BeamformNet: Deep Learning-Based Beamforming Method for DoA Estimation via Implicit Spatial Signal Focusing and Noise Suppression
Xuyao Deng, Yong Dou, Kele Xu
Deep learning-based direction-of-arrival (DoA) estimation has gained increasing popularity. A popular family of DoA estimation algorithms is beamforming methods, which operate by c…
Unify Variables in Neural Scaling Laws for General Audio Representations via Embedding Effective Rank
Xuyao Deng, Yanjie Sun, Yong Dou +1
Scaling laws have profoundly shaped our understanding of model performance in computer vision and natural language processing, yet their application to general audio representation…
Spatial Signal Focusing and Noise Suppression for Direction-of-Arrival Estimation in Large-Aperture 2D Arrays under Demanding Conditions
Xuyao Deng, Yong Dou, Kele Xu
Direction-of-Arrival (DOA) estimation in sensor arrays faces limitations under demanding conditions, including low signal-to-noise ratio, single-snapshot scenarios, coherent source…
AudioSet-R: A Refined AudioSet with Multi-Stage LLM Label Reannotation
Yulin Sun, Qisheng Xu, Yi Su +4
AudioSet is a widely used benchmark in the audio research community and has significantly advanced various audio-related tasks. However, persistent issues with label accuracy and c…