A meta-benchmark that auto-generates multimodal music-perception multiple-choice tests from user symbolic music, demonstrated on ChoraleBricks with text-only and white-noise controls.
Hearing the order: Investigating selection bias in large audio-language models
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Introduces the MUSA benchmark and evaluates LALMs showing that strong single-speaker performance fails to ensure robust selective attention under multilingual interference, with errors from source confusion and unresolved attribution after separation.
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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Music I Care About: Automated Multimodal Benchmarking of LLM Music Perception Skills on (Almost) Any Music
A meta-benchmark that auto-generates multimodal music-perception multiple-choice tests from user symbolic music, demonstrated on ChoraleBricks with text-only and white-noise controls.
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Can Large Audio Language Models Ignore Multilingual Distractors? An Evaluation of Their Selective Auditory Attention Capabilities
Introduces the MUSA benchmark and evaluates LALMs showing that strong single-speaker performance fails to ensure robust selective attention under multilingual interference, with errors from source confusion and unresolved attribution after separation.
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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.