Self-supervised audio models are typically pre-trained on large collections of real-world recordings, and the resulting representations may be shaped by the acoustic coverage, recording conditions, and dataset-specific correlations of the source corpus. We investigate whether procedurally generated audio can provide a...
Feng-Rui Liu, Rui-Yang Huang, Qi-Jian Zheng et al.· IEEE Transactions on Audio,...· 2 citations
As large language models (LLMs) become increasingly widespread, preventing unsafe responses to harmful prompts is essential for their safe deployment. Activation steering offers an approach to improving LLM safety by modifying internal activations during inference without updating model parameters. However, a single pr...
Chen-Xi Wang, Rui-Yang Huang, Li Huang et al.· 0 citations
RefineCut is introduced, which, unlike workflow systems that wrap a prompted frontier model, trains a compact open-weight planner for it, which matches or exceeds its frontier teachers.
Hao-Yu Wang, Cheng Feng, Liuyang Bian et al.· 1 citation
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