Multimodal STEM problem set for verifiable, answer-supervised training and RL: contains single-image, multi-panel, and multi-image PhD-level questions across physics, math, chemistry and biology. Each example has a deterministic ground-truth answer, enabling reward modeling and automated evaluation.
Pairs natural-language instructions with executable setup artifacts and Python reward functions to create verifiable computer-use agent tasks. Provides a Parquet task table for fast filtering plus a compressed archive of runnable task bundles; several web task endpoints are placeholders that require a local CUA-Gym-Hub deployment.
Provides 40 public Kubernetes incident scenarios (SRE subset) with ground-truth root-cause entities and offline cluster snapshots in JSONL format; designed to evaluate agentic root-cause diagnosis on alerts, events, traces and topology.
Provides 9,000 reconstructed chain-of-thought (CoT) SFT examples produced by trace inversion from Claude Opus 4.6 outputs for fine-tuning reasoning-capable LLMs. Multilingual, packaged as .jsonl.gz and SFT/DPO-ready; verify numeric/code cases before training.
Parallel Chinese→Vietnamese dataset of webnovel (xianxia) text provided in JSON for NMT training and teacher-student distillation. In-domain, ~100K–1M examples with CC-BY-4.0 license — useful for fine-tuning or distillation experiments but limited by narrow genre and small download footprint.
Metadata-only corpus of 146.3M new GitHub source-code files (commit_id, rel_path, language) intended as an incremental update to Nemotron v1/v2 for LLM code pretraining; CC-BY-4.0 licensed and designed to be used jointly with older versions.
A collection of 14,056 self-contained research-level mathematical problems extracted from papers and open-problem lists, each rewritten with taxonomy labels and open-status metadata for training or evaluating models on research-grade math reasoning.
Provides a sanitized, MIT‑licensed dataset of scanner evidence and registry verdicts for public ClawHub agent skills — 67k+ latest skill versions with redacted artifacts and structured VirusTotal, static-analysis, and SkillSpector outputs to study scanner disagreement and agent-skill risk governance.
Evaluates metric 3D spatial reasoning from single driving images via multiple-choice questions that require reconstructing scene geometry rather than relying on image-layout shortcuts. Each sample pairs a numbered-bbox image with a question, four choices, and the correct answer; images come from PlusAI and the dataset is CC BY 4.0.
Provides the gated, official OSWorld 2.0 Python task class files (task_*.py) required to run the benchmark; distributed via a Hugging Face gated dataset to reduce benchmark leakage. Download requires accepting gated access on Hugging Face.
Around 80K short audio clips paired with transcripts in JSON, organized for easy loading with the Hugging Face datasets ecosystem—designed for short-form speech tasks (ASR, TTS, fine-tuning) and quick prototyping with common Python data tools.
Provides 600,000 synthetic Vietnamese persona texts (100,000 records, 6 personas per record) aligned to Vietnam's 2024 census and surveys for training and evaluating NLP / text-generation models; includes 21 demographic and persona fields, CC BY 4.0, single train split.