AI Dataset2024
Provides pre-parsed Parquet snapshots of English and French Wikipedia articles with structured fields (sections, infoboxes, tables, references, images) and credibility signals — optimized for large-scale analysis, retrieval-augmented generation, and model development.
AI Dataset2025
Multi‑modal closed-ended academic benchmark with 2,500 multiple-choice and short-answer exam questions spanning math, natural sciences, and humanities for automated grading. Curated by subject-matter experts, released under MIT, and includes a canary string to help prevent dataset leakage into model training.
AI Dataset2025
A curated dataset of ~30,000 CUDA kernels generated by an agentic pipeline, including reference PyTorch implementations, runtime metrics, NCU/Torch/Clang-Tidy profiles, error messages and correctness labels — released under CC-BY-4.0 for model fine-tuning and offline RL/optimization research.
AI Dataset2025
Provides 1.7M+ synthetic and real infographic charts paired with their tabular data for training and evaluating multimodal models on infographic understanding, chart-to-table extraction, chart code generation, and example-based chart synthesis.
AI Dataset2025
A 1,000,000-sample Vietnamese historical conversation dataset in ShareGPT/ChatML format for question-answering and text-generation. Approximately 78% of samples include step-by-step reasoning chains; remaining samples are final-only. Useful for training or evaluating Vietnamese LLMs and chat agents.
AI Dataset2025
Collects ~200,000 human responses to 20 visual/semantic association questions (e.g., Bouba–Kiki), with per-response image options and demographic metadata — useful for cross‑cultural perception and evaluation of multimodal systems, but not guaranteed as a rigorously controlled experimental sample.
AI Dataset2026
Provides 100 real-world, open-ended research tasks paired with expert-written rubrics (around 40 weighted criteria per task) to evaluate long-form, web-browsing research agents on factual accuracy, analysis depth, presentation, and citation quality.
AI Dataset2026
Provides 1.06M web interaction trajectories (state, action, next_state) represented primarily as A11y trees for training browser world models and web agents. Covers diverse real‑web domains, English/Chinese pages, and long contexts (up to 30K tokens); residual PII and dynamic content may limit reproducibility.
AI Dataset2026
Provides 6,000 runnable, operator-level PyTorch tasks for training and evaluating CUDA kernel generation models; each sample includes executable code, operator descriptors, and provenance tags, with execution-driven filtering to ensure reproducibility and contamination control.
AI Dataset2026
Provides a 1,000-row sample user–item interaction Parquet for the TAAC2026 recommendation task, using a flat column layout with 120 top-level columns (IDs, labels, user/item int & dense features, and four-domain behavioral sequences). Updated 2026-04-10.
AI Dataset2026
Large-scale mid-training corpora for multimodal models: 10,809 ~60s video shards, caption splits (30s/60s/180s/>10min), 84 spatial-reasoning shards, and CSV mappings to source YouTube IDs. Small Parquet preview configs are provided for schema inspection.
AI Dataset2026
Provides 336,146 Turkish instruction-following chat examples (system→user→assistant) for supervised fine-tuning; single train split (no validation/test), reported MIT license, diverse tasks (rewrites, summarization, QA) and a uniform system prompt that may bias model behavior.