qwen3-omni-thinking-d6d20c0d·1 events·first seen Aliases: Qwen3-Omni-Thinking
Researchers audit 'protocol-level shortcuts' in large audio-language models (LALMs) used as automatic judges for speech evaluation, testing across three deployment protocols: feature-blueprint judging, reference-conditioned judging, and pairwise A/B comparison. Across six judges and four attributes, several LALMs are found to rely on shortcuts rather than actual audio content — for example, incorrect specialist labels collapse emotion accuracy to 0.10 or below for five judges, and Qwen3-Omni-Thinking shows position bias in A/B comparisons. The findings indicate that high human-agreement scores can overstate judge validity, and that each model-protocol pair requires its own shortcut probe to be trustworthy.