datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
xenia-revocable-feedback
Xenia Cage & Key — Revocable Feedback Atlas
This deterministic candidate contains 32 original synthetic cases in 16 matched pairs.
Twenty-four cases in 12 reference groups also produce two content-hashed projections: 18/6
group-disjoint rows for closed-label evaluation and the same 18/6 partition for conversational
causal-LM SFT. Authorization covers only the 18 'boundary_sft/train' rows. Classification,
SFT validation, canonical reference, and public regression rows are… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/xenia-revocable-feedback.han-human-ai-trust-feedback-dataset-v1
Human–AI Trust Feedback Dataset
This dataset contains human feedback related to trust, comfort,
and reliability when interacting with humanoid AI systems.
It helps Humanoid Network models learn how trust is built,
maintained, or lost during human-AI interactions.
Use Cases
Trust modeling
Ethical AI evaluation
Human-centered system tuning
Fields
interaction_context
human_emotion
trust_level
feedback_text
timestamp
Part of
Humanoid Network (HAN)… See the full description on the dataset page: https://huggingface.co/datasets/achiepatricia/han-human-ai-trust-feedback-dataset-v1.gen-ai-course-feedback
Dataset Card for gen-ai-course-feedback
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/introtogenairize/gen-ai-course-feedback/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/introtogenairize/gen-ai-course-feedback.ai-feedback-dataai-5node-coord-buf-lag-cpl-feedback-spiral-v0.1
What this repo does
This dataset models feedback spirals in multi-agent AI systems. It detects when rising coordination load, weakening safety buffer, governance lag, and tight coupling across agents and tools cross the five-node cascade threshold into an unrecoverable feedback spiral.
This dataset models a five-node cascade: four interacting instability drivers and one emergent cascade state.The fifth node represents the nonlinear transition from recoverable drift to systemic… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-5node-coord-buf-lag-cpl-feedback-spiral-v0.1.hackathon-AI-feedback-dataset