Large streaming-audio dataset for training and evaluating audio-LLMs and audio agents. About 2.28M clips grouped into multi-turn “streams” across six task subsets (ASR, speech translation, audio understanding, voice chat, proactive response, environment-aware); audio shipped as tar shards.
Benchmark for evaluating vision–language models on measurement-grounded inputs vs. RGB, emphasizing low-light, HDR, and visibility-sensitive evidence recovery. Contains 2,183 paired test examples with local image assets for controlled RAW↔RGB comparisons.
Provides ~100 hours of expert-annotated, multi-channel Chinese conversational speech with per-segment timestamps, speaker IDs and paralinguistic labels for turn-taking, overlap/interruption detection and full‑duplex dialogue research. Licensed for academic/non-commercial use (CC BY‑NC 4.0).
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.
Synthesizes high-quality targets for real-world image restoration by using multimodal foundation models (MFMs) to convert real low-quality photos into HQ references. Provides GGT-100K (103,707 LQ–HQ training pairs + 500 test pairs) with multi-stage quality control and demonstrates consistent generalization gains for a range of restoration models, especially for finetuning generative restorers.
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 462 unrestricted long-form chain-of-thought reasoning traces distilled from the full Mythos V2 model (≈104.7M characters); intended for long-context evaluation, trace analysis and process-level supervision. License unknown—verify before reuse.
Provides per-cell transcriptomes and five-day drug-sensitivity readouts for 1.83M single cells across 52 cancer cell lines and 91 drug conditions, with raw counts plus gene, cell-line, drug, and summary metadata for modeling drug response and context-dependent gene function.
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.
A benchmark for evaluating web-browsing agents in Korean contexts, composed of 400 tasks (300 manually verified by native speakers). Includes a human-verified split and an adversarial synthetic split to probe failure modes; reveals large performance gaps for both frontier and Korean models.