Paper recorded by Signals 4 on 2026-09-16 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17
Category: cs.CL · 自然语言处理 · first seen 2026-09-17
Large audio-language models have shown promise for anti-fraud detection by directly processing speech and reasoning over fraud-related evidence. Their deployment, however, requires predictions to follow a predefined label space and a structured decision protocol consisting of service-scenario identification, fraud detection, and conditional fraud-type classification. Existing fine-tuning and promp