Add normalized multimodal interactions and preserved image assets
Browse files
README.md
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- name: images
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list: image
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- name: media_refs
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# pi-embodied Robotics R&D Multimodal Interactions
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This public dataset contains 2,396 project-scoped agent turns, including
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## Storage
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## Media recovery and handling
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Original inline images were recovered from source logs for previously selected turns. Recoverable explicit local image attachments are included. Referenced files that no longer exist remain marked as missing. Remote URLs are not crawled to reconstruct unavailable content. Text is filtered for recognizable credentials and personal identifiers;
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The default `train` split denotes a usable storage split, not a claim that all examples are suitable for supervised training. Outcome-based curation, overlapping-history deduplication, context completion and tool-schema capture remain necessary for individual training recipes. No new redistribution or training license is assigned; original third-party material retains its applicable rights.
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- name: images
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list: image
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- name: media_refs
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sequence: string
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- name: media_status
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dtype: string
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- name: outcome
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# pi-embodied Robotics R&D Multimodal Interactions
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This public dataset contains 2,396 project-scoped agent turns, including 184 turns with recoverable, published images. It preserves successful, unsuccessful, interrupted and unverified interactions without inventing outcome labels.
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## Storage
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## Media recovery and handling
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Original inline images were recovered from source logs for previously selected turns. Recoverable explicit local image attachments are included. Referenced files that no longer exist remain marked as missing. Remote URLs are not crawled to reconstruct unavailable content. Text is filtered for recognizable credentials and personal identifiers. Visual outputs of known robot execution and observation tools are retained with their source provenance; other images undergo OCR filtering for recognizable sensitive content. OCR is a filter rather than a guarantee. Original source logs and withheld images remain on their private source/staging storage.
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The default `train` split denotes a usable storage split, not a claim that all examples are suitable for supervised training. Outcome-based curation, overlapping-history deduplication, context completion and tool-schema capture remain necessary for individual training recipes. No new redistribution or training license is assigned; original third-party material retains its applicable rights.
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data/train-00000-of-00001.parquet
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manifest.json
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