AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces the Multi-control Mixed Audio Generation benchmark, a systematic evaluation protocol that measures acoustic fidelity, speech quality, semantic alignment, and temporal accuracy, and establishes MMAG as a comprehensive benchmark for future research.
MiDashengLM-Gen is an end-to-end framework that couples a pre-trained Large Language Model (LLM) with per-token conditional flow matching for autoregressive, variable-length mixed-audio scene generation and drastically improves speech intelligibility over existing unified models.
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