10,000-hour head-and-wrist egocentric dataset pairing synchronized head and wrist video with left/right 3D hand pose and optional full-body pose; provided in LeRobot/MCAP formats with episode-level semantic annotations and automated de-identification.
A small public sample of egocentric human demonstration video with synchronized 3D hand and body pose annotations for imitation learning and embodied-AI research. Delivered in Parquet and common multimodal packages (LeRobot, MCAP) for schema inspection before requesting gated access to larger EgoSuite releases.
Provides raw, unscripted first-person household video footage for training vision and embodied AI models. Released incrementally on Hugging Face in WebDataset shards with metadata parquets under Apache‑2.0; current raw tier contains ~7,834 hours (≈397k videos).
Provides 90,000 hours of head-mounted egocentric video paired with synchronized 3D hand pose and an optional 3D full‑body pose add-on, with event-level semantic labels available as a complimentary layer — designed for embodied AI and robotics training at scale.
100-hour, single-narrator Egyptian Arabic speech corpus with 15,653 aligned clips at 24 kHz for TTS and ASR fine-tuning; studio-consistent audio, machine-generated undiacritized transcripts, CC BY-NC 4.0 (research/non-commercial use).
Human-annotated text dataset that labels perceived “AI slop” with a continuous human slop_score (-1 / 0 / +1) plus provenance metadata (source_dataset, source_row_id, content_hash). Collected via Bench Labs SlopFinder from public datasets for training classifiers and studying subjective perception.
Provides OCR full text for 11.55M public-domain German newspaper pages (1638–1964) with per-page IIIF scans and ALTO XML coordinates; suited for historical NLP, language-model training, and OCR research. Pages carry explicit per-page public-domain licenses.
Provides a curated benchmark of 170 real-world, multilingual code-refactoring instances to evaluate AI coding agents on large-scale, behavior-preserving, cross-file refactors. Each task includes rewritten issue descriptions and manually reviewed test suites to avoid over- and under-constraining evaluations.
Provides 1,000 five-second video clips generated by MiniMax H3 for lightweight evaluation of multimodal generation and understanding. Clips are roughly 768p base resolution with diverse aspect ratios and themes, produced with a pruned int8 minimax_h3_fl2va checkpoint at 30 steps.
Provides a queryable dataset of 3,797,117 SKILL.md agent-skill files found on public GitHub, deduplicated by content hash and enriched with representative text, front matter, folder composition, repo metadata, and sampled commit history for research.
Provides a year-scale multimodal benchmark and evaluation framework for on-device long-term memory in personal assistants, built from real mobile user trajectories. Tests memory construction, retrieval, updating, temporal reasoning, and implicit preference inference, and includes a knowledge-grounded synthesis pipeline to form coherent long-horizon trajectories.
Provides an L1 filtered English web corpus from recent Common Crawl snapshots for LLM pretraining, including main-text extraction, language and heuristic filtering, sensitive-field replacement, customized cleaning, and MinHash deduplication; contains 1T+ tokens across ~1.14B documents with structured metadata fields.