This work proposes Multi-Role Multi-Agent Debate as a task-specific adaptation of standard multi-agent debate for speaker relationship inference, assigning agents complementary roles or social-theory-grounded perspectives rather than a single undifferentiated viewpoint, and introduces Multi-Agent Compete, a competition...
Yao-Han Guan, Yen-Ju Lu, Yu-Zhe Wang et al.· 0 citations
A scalable framework that identifies text-biased surface interpretations and converts disagreement regions into conflict QA examples and develops an agentic-style reasoning framework that converts speech into an Audio Twin, a text-readable representation of localized acoustic cues that exposes acoustic evidence to the...
Yen-Ju Lu, Yu-Zhe Wang, Yao-Han Guan et al.· 1 citation
It is demonstrated that self-supervised representation reconstruction (SSRR) loss fundamentally improves codec training and performance, and enhances intelligibility by reconstructing distilled self-supervised representations from codec outputs.
Junhyeok Lee, Xiluo He, Jihwan Lee et al.· arXiv.org· 2 citations
This work proposes a practical dataset-aware framework for deepfake detection that relies only on dataset identity as a naturally available supervisory signal for multitask (MT) and gradient reversal layer (GRL) training, allowing the model to investigate both dataset-aware multitask supervision and adversarial suppres...
Mingrui Liang, Thomas Thebaud, Lukasz Wójciak et al.· 0 citations
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