Interleaved SLMs implicitly transcribe spoken words to text tokens in middle layers (top candidate for 77% of data) before predicting in text space and returning to speech.
Do audio llms really listen, or just transcribe? measuring lexical vs. acoustic emotion cues reliance
3 Pith papers cite this work. Polarity classification is still indexing.
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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.
CogAudio-LLM introduces LIME-440K dataset, EIPS chain-of-thought reasoning, and DR-SAPO optimization to address semantic dominance and improve affective responses in audio language models.
citing papers explorer
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Interleaved Speech Language Models Latently Work In Text
Interleaved SLMs implicitly transcribe spoken words to text tokens in middle layers (top candidate for 77% of data) before predicting in text space and returning to speech.
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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.
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Beyond Semantic Dominance: Cognitive Affective Reasoning and Empathetic Response Alignment in Audio Language Models
CogAudio-LLM introduces LIME-440K dataset, EIPS chain-of-thought reasoning, and DR-SAPO optimization to address semantic dominance and improve affective responses in audio language models.