team
Datasets
All datasets matching “team”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.ToolACE
ToolACE
ToolACE is an automatic agentic pipeline designed to generate Accurate, Complex, and divErse tool-learning data.
ToolACE leverages a novel self-evolution synthesis process to curate a comprehensive API pool of 26,507 diverse APIs.
Dialogs are further generated through the interplay among multiple agents, guided by a formalized thinking process.
To ensure data accuracy, we implement a dual-layer verification system combining rule-based and model-based checks.
More details… See the full description on the dataset page: https://huggingface.co/datasets/Team-ACE/ToolACE.pipeline-cctv-analyticsPMC
Data collected from PMC
Only CC-BY, CC-BY-SA licenses are included.
For all records, check the jsonl files in the data folder
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.babilong
BABILong (100 samples) : a long-context needle-in-a-haystack benchmark for LLMs
Preprint is on arXiv and code for LLM evaluation is available on GitHub.
BABILong Leaderboard with top-performing long-context models.
bAbI + Books = BABILong
BABILong is a novel generative benchmark for evaluating the performance of NLP models in
processing arbitrarily long documents with distributed facts.
It contains 11 configs, corresponding to different sequence lengths in tokens:… See the full description on the dataset page: https://huggingface.co/datasets/RMT-team/babilong.