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Long-form thinking traces can substantially improve the multi-step reasoning performance of large language models (LLMs), but they introduce high inference-time overhead, with latency dominated by sequential decoding. We propose HyperThink, a text-to-parameter approach that amortizes this reasoning computation into a s...
The Vector Archive Mapping ECAPA (VAM-ECAPA), a novel system designed to enhance feature extraction from short-duration speech, is proposed, which enriches information-scarce features by mapping them against a learnable Vector Archive of canonical speaker traits.
This work proposes SISER (Speaker-Invariant Speech Emotion Recognition), integrating wav2vec 2.0 as a feature encoder and ECAPA-TDNN as a speaker discriminator within an entropy-based adversarial training scheme.
This work proposes ToolDF, a tool-integrated reasoning framework for mixed-authenticity audio deepfake detection that employs an audio large language model as an orchestrator trained with supervised tool-use trajectories and introduces a mixed-authenticity ADD benchmark covering temporal transitions, acoustic overlaps,...
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