Sparse autoencoders applied to Whisper ASR reveal monosemantic features across linguistic boundaries and demonstrate cross-lingual feature steering.
Librispeech: An ASR corpus based on public domain audio books
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APC embeds compact Ed25519 signatures into audio phase data with error correction to achieve 97.5-98.3% cryptographic verification under eight attack types at mean PESQ 3.02.
GRM ranks Mel bands by attack contribution versus utility sensitivity, perturbs a subset, and learns a universal perturbation to reach 88.46% average jailbreak success rate with improved attack-utility trade-off on four audio LLMs.
GLM-4-Voice builds an end-to-end spoken chatbot by deriving a 175bps single-codebook tokenizer from ASR, synthesizing interleaved speech-text data, and continuing pre-training of GLM-4-9B on up to 1 trillion tokens before fine-tuning on conversational speech.
citing papers explorer
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Mechanistic Interpretability of ASR models using Sparse Autoencoders
Sparse autoencoders applied to Whisper ASR reveal monosemantic features across linguistic boundaries and demonstrate cross-lingual feature steering.
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Asymmetric Phase Coding Audio Watermarking
APC embeds compact Ed25519 signatures into audio phase data with error correction to achieve 97.5-98.3% cryptographic verification under eight attack types at mean PESQ 3.02.
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GRM: Utility-Aware Jailbreak Attacks on Audio LLMs via Gradient-Ratio Masking
GRM ranks Mel bands by attack contribution versus utility sensitivity, perturbs a subset, and learns a universal perturbation to reach 88.46% average jailbreak success rate with improved attack-utility trade-off on four audio LLMs.
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GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot
GLM-4-Voice builds an end-to-end spoken chatbot by deriving a 175bps single-codebook tokenizer from ASR, synthesizing interleaved speech-text data, and continuing pre-training of GLM-4-9B on up to 1 trillion tokens before fine-tuning on conversational speech.