AI Dataset2024
A fine-grained, domain-labeled web corpus for NLP and LLM research that decomposes a deduplicated web crawl into 67 domains via iterative URL/content labeling and coarse→fine recall; includes per-domain statistics, validation subsets, and domain-benchmark analysis tools.
AI Dataset2026
Provides over 1.1M hours of high-bandwidth, multichannel multilingual speech with segment- and word-level timestamps, English translations, and per-file metadata for ASR, TTS and audio-representation research. Preserves original 48kHz multichannel OPUS audio and is released under CC BY 3.0.
AI Dataset2026
Provides 1.21M densely annotated desktop screenshots and 159.7M element instances for training and evaluating GUI grounding and screen-parsing models. Includes per-element accessibility-derived annotations, 917K recorded click transitions, multi-application scenes across seven appearance presets and resolutions; distributed as WebDataset shards with Parquet indexes.
AI Dataset2026
Provides a unified, camera-conditioned, multi-source video dataset and reproducible processing pipeline for training long-horizon video world models. Key features: a canonical frame-aligned contract (visuals, camera geometry, captions, quality metadata), 1.43M canonical clips with portable releases and reconstruction tools; large download and some backbone assets carry separate licenses.
AI Dataset2026
Provides a dual-channel, channel-separated sample (8.9 hours) and access path to a 1,000‑hour English conversational corpus for commercial and research use. Delivers 48 kHz per-speaker audio, word-level machine transcripts, and per-speaker metadata designed for full‑duplex/turn-taking and ASR/ TTS research.
Jaihyun Lew, Mingi Jung +3Interdisciplinary Program in AI, Seoul National University, Department of Electrical and Computer Engineering, Seoul National University +1
Uses diffusion-model forking moments as a proxy for perceptual distance to automatically generate pointwise reference-grounded labels, enabling annotation-free training of reference-based image quality assessment metrics.