CodecAttack perturbs audio in codec latent space with multi-bitrate EoT to achieve 85.5% average ASR on Opus-compressed Audio LLMs versus under 26% for waveform baselines, with transfer to MP3 and AAC.
Pengi: An audio language model for audio tasks
3 Pith papers cite this work, alongside 20 external citations. Polarity classification is still indexing.
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A learned per-example router over a 105-perturbation audio library improves contrastive decoding for audio-LLM hallucination, with task-dependent best distortions (e.g., reverse audio for temporal order).
Audio language models are benchmarked on five semantic and paralinguistic reasoning tasks to reveal limitations in handling spoken audio evidence, accent variation, and domain shifts.
citing papers explorer
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Codec-Robust Attacks on Audio LLMs
CodecAttack perturbs audio in codec latent space with multi-bitrate EoT to achieve 85.5% average ASR on Opus-compressed Audio LLMs versus under 26% for waveform baselines, with transfer to MP3 and AAC.
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Adaptive Perturbation Selection for Contrastive Audio Decoding
A learned per-example router over a 105-perturbation audio library improves contrastive decoding for audio-LLM hallucination, with task-dependent best distortions (e.g., reverse audio for temporal order).
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Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents
Audio language models are benchmarked on five semantic and paralinguistic reasoning tasks to reveal limitations in handling spoken audio evidence, accent variation, and domain shifts.