Provides page-level relevance judgments and full OCR'd annual-report text for KPI question answering and page retrieval benchmarking — supports retrieval (per-page qrels) and needle‑in‑a‑haystack numeric extraction over long documents, with eval and train configs.
Pairs OCR-extracted annual-report text with ground-truth financial KPI values to benchmark LLM/table-QA and needle-in-a-haystack extraction tasks. Includes Markdown OCR (.mmd), page images for eval, and 31 KPI columns across multiple years—suited for KPI extraction, retrieval, and robustness testing.
Provides 1,036,431 identity–text–video triplets with per-video JSON annotations and reference keyframes to train and evaluate identity-preserving customized video generation models. Data is drawn from ~320K Pexels HD videos; videos must be downloaded separately per Pexels' terms.
Provides 500+ hours of human whole-body teleoperation demonstrations for humanoid robot learning in real homes, with synchronized video, joint states, action traces and language annotations. Includes 23K+ episodes, fine-grained subtask labels, and raw ROS/MCAP plus compressed LeRobot formats.
Provides 500+ hours of human whole-body teleoperation recordings of a Unitree G1 in real homes, packaged in LeRobot v3.0 for robot learning. Contains 23K+ episodes, ~40M frames, multi-view 480p@30 video, 29-DoF states, actions and language annotations; CC BY 4.0 and large download size.
Provides a token-level benchmark for Russian PII detection and NER, with 2,841 sentences and 5,614 annotated spans across 21 fine-grained entity types in BIO format. Mixes sanitized production-log examples, synthetic document templates, and hard negatives to evaluate guardrails and anonymization pipelines.
Contains a sanitized Claude Code (Fable 5) JSONL transcript of a session that procedurally built a Boeing 747 in Three.js, including assistant messages, tool calls, and base64 screenshots — useful for studying agent trace, tool use, and vision self‑verification workflows.
Refines large-scale English pretraining corpora by predicting per-instance structured edits (insert, delete, replace) and deterministically applying them to produce cleaner text for LLM training. Provides five ~20B-token refined corpora in parquet with edit metadata and simple loading configs.
Anonymized agent-trace JSONL capturing conversations, tool calls, and function schemas from Claude fable-5 (Claude Code) runs — packaged for fine-tuning, distillation, and building tool-aware assistants; compatible with teich for conversion to OpenAI-style chats.
Provides 1000+ hours of high-precision optical motion-capture for humanoid robotics and embodied AI, including full-body skeleton, 20+DoF hands, object 6D, and multi-view video at 120 Hz. Sub-mm spatial accuracy, BVH/CSV/NPZ outputs and Unitree G1 retargets; ideal for imitation learning and sim-to-real, with some raw captures gated by license.
Benchmark for evaluating multimodal LLM safety in Korean cultural contexts — includes KSAFE-MM-G which localizes global safety queries into Korean scenarios and KSAFE-MM-C which targets culture-specific visual-textual vulnerabilities. Provides curated image–text pairs and jailbreak-style prompts to reveal both unsafe behaviors and over-refusal.
Provides kanji-level evaluation data for Japanese TTS: disambiguated sentence contexts targeting 4,378 kanji-reading pairs (2,136 Jōyō kanji) with 13,095 native-speaker–verified sentences and katakana-marked ground-truth readings for kanji-level error metrics.