OpenMOSS
Datasets
All datasets matching “OpenMOSS”OmniAction
RoboOmni: Proactive Robot Manipulation in Omni-modal Context
📖 arXiv Paper (Accepted to ICLR 2026 🎉) |
🌐 Website |
🤗 Model |
🤗 Dataset |
🛠️ Github |
Recent advances in Multimodal Large Language Models (MLLMs) have driven rapid progress in Vision–Language–Action (VLA) models for robotic manipulation. Although effective in many scenarios, current approaches largely rely on explicit instructions, whereas in real-world interactions, humans rarely issue… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/OmniAction.OmniAction-LIBERO
RoboOmni: Proactive Robot Manipulation in Omni-modal Context
📖 arXiv Paper (Accepted to ICLR 2026 🎉) |
🌐 Website |
🤗 Model |
🤗 Dataset |
🛠️ Github |
Recent advances in Multimodal Large Language Models (MLLMs) have driven rapid progress in Vision–Language–Action (VLA) models for robotic manipulation. Although effective in many scenarios, current approaches largely rely on explicit instructions, whereas in real-world interactions, humans rarely issue… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/OmniAction-LIBERO.moss-003-sft-data
moss-003-sft-data
** More information: MOSS Paper**
Conversation Without Plugins
Categories
Category
# samples
Brainstorming
99,162
Complex Instruction
95,574
Code
198,079
Role Playing
246,375
Writing
341,087
Harmless
74,573
Others
19,701
Total
1,074,551
Others contains two categories: Continue(9,839) and Switching(9,862).The Continue category refers to instances in a conversation where the user asks the system to continue… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/moss-003-sft-data.GameQA-140K
🎊 News
[2026/07] 🔥Peking University and Kuaishou Kling Team evaluate their agentic visual reasoning method Beacon on our GameQA benchmark. Beacon learns when tools are truly needed (Mode Adaptiveness) and how tool use extends capability on hard problems (Tool Effect), and achieves the highest accuracy on GameQA among open-source models of the same scale, significantly outperforming its Qwen3-VL-8B-Instruct base.
[2026/07] 🔥Peking University and WeChat AI use our Game-RL data… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/GameQA-140K.SWE-bench-Science
SWE-bench Science
SWE-bench Science evaluates coding agents on software-engineering tasks drawn from scientific-computing repositories. The release contains 119 tasks across 20 scientific domains, with isolated environments and separate programmatic verifiers.
GitHub release repository: OpenMOSS/SWE-bench-Science
Runtime images: Docker Hub, pinned by immutable linux/amd64 digests
Evaluation framework: Pier, compatible with Harbor task format
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/SWE-bench-Science.OmniAction-LIBERO-eval