Daily-Omni is an audio–visual question-answering benchmark for audio-visual reasoning that emphasizes temporal alignment across modalities. According to the dataset repository and paper listing, Daily-Omni comprises real-world short videos of daily-life scenarios and multiple-choice QA pairs designed to require integration of audio and visual streams. The project provides a QA generation pipeline (automatic annotation, QA generation and QA optimization) to scale creation and human evaluation, and includes a baseline agent (Daily-Omni-Agent) combining open-source visual-language, audio-language and ASR models with simple temporal alignment methods. The dataset listing on Hugging Face and the project repository report the benchmark contains 684 videos and 1,197 multiple-choice QA pairs across six main task categories (question-answering tasks focused on audio-visual integration).
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