ai-feedback
xenia-revocable-feedback-smollm2-135mavylor-mh_feedback_model-GGUFsentiment_analysis_for_customer_feedbackSmolVLM2-500M-Video-Instruct-video-feedbackT2M-AI-Feedback-3B-RLsentiment-analysis-for-student-feedback-analysistext-summarization-for-customer-feedbacksentiment-analysis-for-parent-feedback-on-schools
daily-paper-2026-09-12-cost-mirror-agent-cost-feedback
The Cost Mirror: Measuring How Live Token-Cost Feedback Changes the Spend, Strategy, and Quality of Unattended LLM Agent Loops
TL;DR — We formalize the cost mirror - surfacing a live per-task token cost to an unattended LLM agent in context, converting metering from a billing read surface into an in-loop control signal - as an induced Lagrange multiplier on the agent's cost-quality objective, bound its reach (mirror ceiling), order its spend channels (cheapest slack first, with… See the full description on the dataset page: https://huggingface.co/datasets/thaki-AI/daily-paper-2026-09-12-cost-mirror-agent-cost-feedback.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.customer-feedback-action-plans
Customer Feedback → Action Plans
A small, practical dataset that maps raw customer feedback (e.g., restaurant reviews) to actionable recommendations with optional aspect annotations and reasoning. Useful for training instruction-following models, aspect-aware summarizers, or classification heads that support the generation task.
Files & Splits
train.csv — main training split for generation.
validation.csv — validation split for generation.
train_aux_classification.csv —… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/customer-feedback-action-plans.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-data