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Download README.md from Berkeley-ICON-Lab/ALTER-data: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
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https://huggingface.co/datasets/Berkeley-ICON-Lab/ALTER-data/resolve/main/README.md
- Command line
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hf download hf://datasets/Berkeley-ICON-Lab/ALTER-data/README.md
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curl -L -o README.md https://huggingface.co/datasets/Berkeley-ICON-Lab/ALTER-data/resolve/main/README.md
2.18 kB
| license: cc-by-4.0 | |
| # ALTER simulation data card | |
| Authors: Dayi Dong, Maulik Bhatt, Aayushi Shrivastava, Lasse Peters, Negar Mehr. | |
| The pretraining selection contains 400 demonstrations: 200 place-return and 200 | |
| wipe. Adaptation includes 60 selected multi-arm demonstrations and 60 distilled | |
| single-arm rollouts at the largest budget. Nested manifests retain 20+20, | |
| 40+40, and 60+60 membership, mode grouping and ordering. FT-multi omits the | |
| single-arm adaptation domain. Counts exclude base-policy pretraining. | |
| Data and provenance retain distinct namespaces. Portable manifests use logical | |
| artifact references; materialization checks checksums and preserves list order. | |
| Do not rerank examples from relocated absolute paths. Original private records | |
| remain retained separately, and exports record original and export hashes. | |
| Use only with the matching model/preprocessing, camera and action conventions | |
| in the release source. Data are trusted Python pickle artifacts, not a safe | |
| format for arbitrary untrusted downloads. Hardware recordings are released separately under `hardware/v1/`; scored physical-trial | |
| evidence is not included. Original ALTER demonstrations, replay and accompanying | |
| original records are released under CC BY 4.0; see LICENSE and NOTICE. Third-party | |
| software, assets and the paper retain their separate terms. | |
| The provenance bundle contains selected evaluation/selection evidence, not new | |
| experimental results. The original base-training contract is absent, and the | |
| FT-mixed selection-panel wording requires author review. No complete paper | |
| retraining or full evaluation rerun is claimed by preparation tests. | |
| See USAGE.md for downloads and the accompanying code release status. | |
| Paper: [Residual Denoising Enables Sample-Efficient Multi-Agent Coordination on Demand](https://arxiv.org/abs/2609.32129). | |
| ## Hardware v1 | |
| Selected hardware models, source data and exact prepared caches are now available | |
| under [hardware/v1](hardware/v1/README.md). See the [hardware download guide](hardware/v1/USAGE.md) | |
| for the separate pinned manifest, selective downloads and offline validation. | |
| Simulation payloads and their pinned revisions remain unchanged. | |