--- license: apache-2.0 task_categories: - question-answering language: - en pretty_name: Deaftest size_categories: - n<1K dataset_info: features: - name: question_id dtype: string - name: question_type_id dtype: string - name: data_type dtype: string - name: subfield dtype: string - name: question dtype: string - name: options sequence: string - name: answer dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: video_1 dtype: string - name: audio_1 dtype: audio - name: audio_2 dtype: audio - name: audio_3 dtype: audio - name: audio_4 dtype: audio splits: - name: test num_bytes: 2722106.18 num_examples: 400 download_size: 2715938 dataset_size: 2722106.18 configs: - config_name: default data_files: - split: test path: deaftest.parquet --- Official Deaftest dataset for the paper "[AV-Odyssey: Can Your Multimodal LLMs Really Understand Audio-Visual Information?]()". 🌟 For more details, please refer to the project page with data examples: [https://av-odyssey.github.io/](https://av-odyssey.github.io/). [[🌐 Webpage](https://av-odyssey.github.io/)] [[📖 Paper]()] [[🤗 Huggingface AV-Odyssey Dataset](https://huggingface.co/datasets/AV-Odyssey/AV_Odyssey_Bench)] [[🤗 Huggingface Deaftest Dataset](https://huggingface.co/datasets/AV-Odyssey/Deaftest_dataset)] [[🏆 Leaderboard](https://huggingface.co/spaces/AV-Odyssey/AV_Odyssey_Bench_Leaderboard)] --- ## 🔥 News * **`2024.11.24`** 🌟 We release AV-Odyssey, the first-ever comprehensive evaluation benchmark to explore whether MLLMs really understand audio-visual information. ## 👀 About AV-Odyssey Recently, multimodal large language models (MLLMs), such as GPT-4o, Gemini 1.5 Pro, and Reka Core, have expanded their capabilities to include vision and audio modalities. While these models demonstrate impressive performance across a wide range of audio-visual applications, our proposed **DeafTest** reveals that MLLMs often struggle with simple tasks humans find trivial: 1) determining which of two sounds is louder, and 2) determining which of two sounds has a higher pitch. Motivated by these observations, we introduce **AV-Odyssey Bench**. This benchmark encompasses **26** different tasks and **4,555** carefully crafted problems, each incorporating text, visual, and audio components. All data are **newly collected and annotated by humans**, not from any existing audio-visual dataset. AV-Odyssey Bench demonstrates three major features: 1. **Comprehensive** Audio Attributes; 2. **Extensive** Domains; 3. **Interleaved** Text, Audio, and Visual components. ## 📐 Data Examples Please refer to our project page https://av-odyssey.github.io/ for exploring more examples. ### 📍AV-Odyssey Bench
## 🔍 Dataset **License**: ``` AV-Odyssey is only used for academic research. Commercial use in any form is prohibited. The copyright of all videos belongs to the video owners. If there is any infringement in AV-Odyssey, please email libohao1998@gmail.com and we will remove it immediately. Without prior approval, you cannot distribute, publish, copy, disseminate, or modify AV-Odyssey in whole or in part. You must strictly comply with the above restrictions. ``` Please send an email to **[libohao1998@gmail.com](mailto:libohao1998@gmail.com)**. 🌟 ## 🔮 Evaluation Pipeline ## 🏆 Leaderboard ### Contributing to the AV-Odyssey Leaderboard 🚨 The [Leaderboard](https://huggingface.co/spaces/AV-Odyssey/AV_Odyssey_Bench_Leaderboard) for AV-Odyssey is continuously being updated, welcoming the contribution of your excellent MLLMs! ## :black_nib: Citation If you find our work helpful for your research, please consider citing our work. ```bibtex ```