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🎵 AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficient Inference in Multimodal LLMs Abstract AudioMarathon is a large-scale, multi-task audio understanding benchmark designed to systematically evaluate audio language models’ capabilities in processing and comprehending long-form audio content. It provides a diverse set of 10 tasks built upon three pillars: long-context audio inputs with durations ranging from 90.0 to 300.0… See the full description on the dataset page:

Source: Hugging Face Hub (Hezep/AudioMarathon). Metadata imported from the dataset’s Hub tags.

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