Dataset · Hugging Face

jinzhuoran/OmniRewardData

Name: OmniRewardData
Creator: jinzhuoran
License: cc-by-nc-4.0
Keywords: task_categories:any-to-any, task_categories:text-generation, task_categories:image-text-to-text, task_categories:text-to-image, task_categories:text-to-video, task_categories:reinforcement-learning, license:cc-by-nc-4.0, size_categories:100K<n<1M, format:parquet, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2510.23451

Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences 📚 Paper | 💻 Code | 🏠 Homepage | 🤗 Benchmark | 🤗 Model Overview High-quality and diverse human preference data is crucial for training effective omni-modal reward models(RMs). However, existing preference datasets are often limited in scope because they focus on specific tasks or general preferences. This limitation hinders the model’s ability to generalize to… See the full description on the dataset page: https://huggingface.co/datasets/jinzhuoran/OmniRewardData.

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Author / organization	jinzhuoran
License (as declared)	cc-by-nc-4.0
Downloads	1.6K (as reported by Hugging Face)
Likes	2
Created	14 May 2025
Last updated at source	29 October 2025

Omni-ModalAlignmentRewardmultimodalpreference-datasetreward-modelingtext-to-audiotext-to-3dimage-text-to-image

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16 Oct 2026 Description: Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences 📚 Paper | 💻 Code | 🏠 Homepage | 🤗 Benchmark | 🤗 Model Overview High-quality and diverse human preference data is crucial for training effective omni- → Omni-Reward: Towards Generalist Omni-Modal Reward Modeling with Free-Form Preferences 📚 Paper | 💻 Code | 🏠 Homepage | 🤗 Benchmark | 🤗 Model Overview High-quality and diverse human preference data is crucial for training effective omni-

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