mcshao/LAT-Bench

LAT-Bench LAT-Bench is the first benchmark designed for evaluating temporal awareness in long-form audio understanding. Unlike existing benchmarks limited to short clips, LAT-Bench supports audio durations up to 30 minutes, enabling evaluation under realistic long-form scenarios. The benchmark covers three core tasks: Dense Audio Captioning (DAC): generate temporally grounded descriptions over the full audio Temporal Audio Grounding (TAG): localize relevant time spans for a… See the full description on the dataset page: https://huggingface.co/datasets/mcshao/LAT-Bench.

<iframe src="https://silytics.si/embed/item/f11cb070-f89b-4c4f-ac6d-2710ffc291ec" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.