ZEBRA reduces the base-to-novel generalization gap in audio-language models by fusing zero-shot and prompt-learning logits with entropy regularization.
Pengi: An audio language model for audio tasks
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A survey of Large Audio Language Models that establishes a taxonomy of trustworthiness vulnerabilities and proposes a Defense-in-Depth roadmap for audio intelligence.
citing papers explorer
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ZEBRA: Zero-Shot Entropy-Regularized Prompt Learning for Base-to-Novel Generalization in Audio-Language Models
ZEBRA reduces the base-to-novel generalization gap in audio-language models by fusing zero-shot and prompt-learning logits with entropy regularization.
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A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook
A survey of Large Audio Language Models that establishes a taxonomy of trustworthiness vulnerabilities and proposes a Defense-in-Depth roadmap for audio intelligence.