--- dataset_info: - config_name: candidates features: - name: did dtype: string - name: text list: string - name: media_id dtype: string splits: - name: train num_bytes: 931441504 num_examples: 7119841 download_size: 499532524 dataset_size: 931441504 - config_name: instructions features: - name: task_id dtype: int32 - name: dataset_id dtype: int32 - name: prompts dtype: string splits: - name: train num_bytes: 28058 num_examples: 58 download_size: 11004 dataset_size: 28058 - config_name: media_shard_000000 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 122849524199 num_examples: 200000 download_size: 122853793676 dataset_size: 122849524199 - config_name: media_shard_000001 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117985237498 num_examples: 200000 download_size: 117988606222 dataset_size: 117985237498 - config_name: media_shard_000002 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117669748066 num_examples: 200000 download_size: 117673236807 dataset_size: 117669748066 - config_name: media_shard_000003 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117765874023 num_examples: 200000 download_size: 117769664261 dataset_size: 117765874023 - config_name: media_shard_000004 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117586015352 num_examples: 200000 download_size: 117590569299 dataset_size: 117586015352 - config_name: media_shard_000005 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 118252475623 num_examples: 200000 download_size: 118255300760 dataset_size: 118252475623 - config_name: media_shard_000006 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117639713891 num_examples: 200000 download_size: 117643189579 dataset_size: 117639713891 - config_name: media_shard_000007 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117427707334 num_examples: 200000 download_size: 117431098509 dataset_size: 117427707334 - config_name: media_shard_000008 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 118041395077 num_examples: 200000 download_size: 118046142117 dataset_size: 118041395077 - config_name: media_shard_000009 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117724310015 num_examples: 200000 download_size: 117728340239 dataset_size: 117724310015 - config_name: media_shard_000010 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117390521616 num_examples: 200000 download_size: 117395658377 dataset_size: 117390521616 - config_name: media_shard_000011 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117439367419 num_examples: 200000 download_size: 117444566123 dataset_size: 117439367419 - config_name: media_shard_000012 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 118444042857 num_examples: 200000 download_size: 118449572108 dataset_size: 118444042857 - config_name: media_shard_000013 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117590368881 num_examples: 200000 download_size: 117594645617 dataset_size: 117590368881 - config_name: media_shard_000014 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117985815582 num_examples: 200000 download_size: 117990857457 dataset_size: 117985815582 - config_name: media_shard_000015 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117263260177 num_examples: 200000 download_size: 117267034089 dataset_size: 117263260177 - config_name: media_shard_000016 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 117574792839 num_examples: 200000 download_size: 117579302317 dataset_size: 117574792839 - config_name: media_shard_000017 features: - name: media_id dtype: string - name: image dtype: image - name: video list: image - name: audio dtype: binary - name: has_audio dtype: bool splits: - name: train num_bytes: 81693044328 num_examples: 138323 download_size: 81696151897 dataset_size: 81693044328 - config_name: queries features: - name: id dtype: string - name: task_id dtype: int32 - name: text list: string - name: media_id dtype: string - name: candidates list: string splits: - name: train num_bytes: 834160494 num_examples: 6405109 download_size: 366840294 dataset_size: 834160494 configs: - config_name: candidates data_files: - split: train path: candidates/train-* - config_name: instructions data_files: - split: train path: instructions/train-* - config_name: media_shard_000000 data_files: - split: train path: media_shard_000000/train-* - config_name: media_shard_000001 data_files: - split: train path: media_shard_000001/train-* - config_name: media_shard_000002 data_files: - split: train path: media_shard_000002/train-* - config_name: media_shard_000003 data_files: - split: train path: media_shard_000003/train-* - config_name: media_shard_000004 data_files: - split: train path: media_shard_000004/train-* - config_name: media_shard_000005 data_files: - split: train path: media_shard_000005/train-* - config_name: media_shard_000006 data_files: - split: train path: media_shard_000006/train-* - config_name: media_shard_000007 data_files: - split: train path: media_shard_000007/train-* - config_name: media_shard_000008 data_files: - split: train path: media_shard_000008/train-* - config_name: media_shard_000009 data_files: - split: train path: media_shard_000009/train-* - config_name: media_shard_000010 data_files: - split: train path: media_shard_000010/train-* - config_name: media_shard_000011 data_files: - split: train path: media_shard_000011/train-* - config_name: media_shard_000012 data_files: - split: train path: media_shard_000012/train-* - config_name: media_shard_000013 data_files: - split: train path: media_shard_000013/train-* - config_name: media_shard_000014 data_files: - split: train path: media_shard_000014/train-* - config_name: media_shard_000015 data_files: - split: train path: media_shard_000015/train-* - config_name: media_shard_000016 data_files: - split: train path: media_shard_000016/train-* - config_name: media_shard_000017 data_files: - split: train path: media_shard_000017/train-* - config_name: queries data_files: - split: train path: queries/train-* --- # OmniRet training dataset `OmniRet-train` is the training-data release for [OmniRet](https://arxiv.org/abs/2603.02098), a unified retrieval model for text, image, video, and audio. This card documents the released snapshot for researchers training or analyzing OmniRet. ## Dataset summary The release contains 6,405,109 query rows and 7,119,841 candidate rows from 30 datasets. It covers 15 retrieval directions across text (T), image (I), video (V), and audio (A). The OmniRet paper reports this corpus as approximately 6.4 million query-candidate pairs. ## Provenance OmniRet starts from the [M-BEIR](https://huggingface.co/datasets/TIGER-Lab/M-BEIR) universal retrieval benchmark and extends it with text, image-text, video-text, audio-text, and audio-visual training data. The source groups follow the training-data section and Table 10 of the [OmniRet paper](https://arxiv.org/abs/2603.02098). | Source group | Datasets | | --- | --- | | M-BEIR foundation | NIGHTS, WebQA, VisualNews, Fashion200K, MSCOCO, EDIS, OVEN, InfoSeek, FashionIQ, CIRR | | Added text retrieval | MS MARCO, HotpotQA, Natural Questions, PAQ, StackExchange, NLI, SQuAD | | Added image-text and composed image retrieval | LLaVA-558K, CC-CoIR, MTCIR | | Added video-text and composed video retrieval | TGIF, Charades, WebVid2M, PE-Video, WebCoVR | | Added audio-text retrieval | AudioCaps, Clotho v2.1, WavText5K, WavCaps | | Added audio-visual retrieval | VGGSound | ## Retrieval tasks | Family | Directions | | --- | --- | | Unimodal | I → I; T → T | | Cross-modal binding | I → T; T → I; V → T; T → V; A → T; T → A | | Composed retrieval | T → (I,T); (I,T) → T; (I,T) → I; (I,T) → (I,T); (V,T) → V | | Audio-visual binding | A → V; V → A | ## Repository layout | Path | Contents | | --- | --- | | `queries/` | Training queries, task IDs, positive candidate IDs, text, and media references | | `candidates/` | Candidate records referenced by the queries | | `instructions/` | Retrieval instructions keyed by task and dataset | | `media_shard_*/` | Sharded image, video, and audio payloads | | `metadata/candidate_index.sqlite` | Read-only lookup index for 7,119,841 candidates | | `metadata/media_index.sqlite` | Read-only lookup index for 3,538,323 media IDs across 1,976 Parquet files | | `metadata/train_pairs.jsonl` | Precomputed manifest containing 6,405,109 training pairs | Download the repository to the canonical training path: ```bash hf download chuonghm/OmniRet-train \ --repo-type dataset \ --local-dir /data1/omniret/OmniRet-train-data ``` The published media index stores Parquet paths below `/data1/omniret/OmniRet-train-data`. Use that location, or provide a compatible media index when using another root. ## Relationship to the ACM benchmark The OmniRet paper also introduces the separate [Audio-Centric Multimodal benchmark (ACM)](https://huggingface.co/datasets/chuonghm/ACM), curated from VGGSound. ACM evaluates composed audio retrieval (A,T → A) and bidirectional audio-image and audio-video retrieval (A → I, I → A, A → V, V → A). Use `chuonghm/ACM` for evaluation; this training repository does not replace the benchmark release. ## Data terms This repository is a transformed compilation of upstream datasets. Underlying examples remain subject to their original licenses and terms. Review the [M-BEIR dataset card](https://huggingface.co/datasets/TIGER-Lab/M-BEIR) and the source references in Table 10 of the [OmniRet paper](https://arxiv.org/abs/2603.02098) before redistribution or commercial use. ## Citation Please cite OmniRet for this extended training release and ACM benchmark, and cite UniIR for the M-BEIR foundation. ```bibtex @article{huynh2026omniret, title = {Efficient and High-Fidelity Omni Modality Retrieval}, author = {Huynh, Chuong and Luong, Manh and Shrivastava, Abhinav}, journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026} } @article{wei2023uniir, title = {UniIR: Training and Benchmarking Universal Multimodal Information Retrievers}, author = {Wei, Cong and Chen, Yang and Chen, Haonan and Hu, Hexiang and Zhang, Ge and Fu, Jie and Ritter, Alan and Chen, Wenhu}, journal = {arXiv preprint arXiv:2311.17136}, year = {2023} } ```