Audio LLMs Know When They Can't Hear You

arXiv:2609.30625 · cs.AI · Submitted 2026-09-24 · Read on arXiv

cs.AI

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Accuracy — 52× in this paper · explained in 1 episode
• Alignment — 10× in this paper · explained in 1 episode
• Aggregation — 8× in this paper · explained in 1 episode
• Cross-Model Transfer — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Generalization — 5× in this paper · explained in 13 episodes
• Computational overhead — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• In-Context Learning — 2× in this paper · explained in 4 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Signal-to-noise ratio (SNR) — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Production Quality — 1× in this paper

Sources

• Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
• Qwen2-Audio Technical Report
• Language Models (Mostly) Know What They Know
• MUSAN: A Music, Speech, and Noise Corpus
• Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound
• MOSS-Audio Technical Report

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