datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CN-AEBench
Notice: This repository is currently public, and we will remove the “Access requests” option immediately upon paper acceptance. This setting is implemented solely because, unlike Science Data Bank, Hugging Face does not offer draft or release protection statuses.
If you are interested in our work, please contact AI_weather@126.com to obtain early access.
CN-AEBench is a comprehensive multi-source atmospheric & environmental dataset integrating ground meteorological observations… See the full description on the dataset page: https://huggingface.co/datasets/AIWeather126/CN-AEBench.pwn-scenarios
pwn-scenarios
36,457 records, 47 vulnerability classes. A dataset of penetration testing / bug bounty scenarios -- generalized, reusable condition → step → impact → remediation playbooks for common vulnerability classes, each grounded in a real, publicly disclosed report or writeup.
Full source, collection scripts, the companion attack decision graph, and complete docs live on GitHub: https://github.com/AlaBYahya/pwn-scenarios
Example record
{
"vulnerability":… See the full description on the dataset page: https://huggingface.co/datasets/aeby/pwn-scenarios.aeb-verification-captures
Camera frames and trained networks for the braking verification study
The inputs to AD-Assurance-Lab/formal-verification--aeb--code, measured on 2026-09-10.
Why this exists. The study's results are in git. These files are not: they are large and
git ignores them. Without them the published numbers can be reproduced in kind but never
exactly, because the simulator does not render bit-identical frames from one run to the
next. Different frames give different networks, which give… See the full description on the dataset page: https://huggingface.co/datasets/AD-Assurance-Lab/aeb-verification-captures.aebn-vod-downloader-v2
aebn-vod-downloader v2
Python VOD downloader with a local web UI. v2 keeps the proven native segment
engine and rebuilds the service layer around it: pluggable subtitle backends,
an optional yt-dlp engine, hardened job lifecycle, and defaults sized for a
32-core / 64 GB node on a high-speed private tailnet.
What changed from web-ui (v0.10.1)
RunPod is no longer the default or a hard dependency. Subtitle generation
is now a pluggable, selectable service: openai… See the full description on the dataset page: https://huggingface.co/datasets/jblast94/aebn-vod-downloader-v2.africa-comoros-comoros-social-protection-and-labor-aebfb39a
Comoros - Social Protection and Labor | Africa (Comoros official open data)
3,191 rows - 1 Africa country - 1980-2025 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Comoros as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
Source: Comoros - Social Protection and Labor… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-comoros-comoros-social-protection-and-labor-aebfb39a.aeb_tdu_Atomic20peraeb_tdu_AtomicImmersive5000_10aeb_tdu_AtomicFullAEB_1_EMOLLM
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_ex02
Dataset Card for "aeb_tdu_ex02"
More Information needed
aeb_tdu_Atomic10peraeb_tdu_exInvalid50Peraeb_tdu_Atomic40peraeb_tdu_Atomic50peraeb_tdu_AtomicImmersive30aebsaaeb_tdu_exInvalid40PerAEB_2_FT
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_exRef2aeb_tdu_ex03aeb_tdu_AtomicImmersive10000_8-12aeb_tdu_Atomic30perAEB_1_FT
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_exRefAEB_1_ZS
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_ex04aeb_tdu_AtomicImmersive40examples-condenser-detectionAEB_1_FS
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
AEB_2_ZS