datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wearable-agent-trajectory-annotations
Wearable Agent Trajectory Annotation Dataset
Dataset Summary
50 wearable agent trajectories annotated by 5 LLM-simulated annotator personas
using the agenteval-schema-v1 JSON schema, across two calibration phases
(500 annotation records total). Designed to benchmark annotation-quality pipelines
for agentic AI systems.
Each trajectory captures a wearable AI agent responding to a real-time sensor event
(health alert, privacy-sensitive context, location trigger… See the full description on the dataset page: https://huggingface.co/datasets/finaspirant/wearable-agent-trajectory-annotations.crowdsourced-vru-annotations
Crowdsourced VRU Annotations
Dataset Summary
This dataset provides tabular annotations from two underlying datasets — ECP and ZOD — and is organized into two splits (ecp and zod).It contains the results of crowdsourced annotation tasks focusing on vulnerable road users (VRUs).
The underlying examples are image crops showing bounding boxes of VRUs from the ECP and ZOD datasets. Each crop is referenced via a crop_id. The actual image pixels are not included in this… See the full description on the dataset page: https://huggingface.co/datasets/cklugmann/crowdsourced-vru-annotations.DAM-QA-annotations
DAM-QA Unified Annotations
22,675 question-answer pairs from 6 major VQA benchmarks, unified for the DAM-QA framework. This collection consolidates annotations from InfographicVQA, TextVQA, VQAv2, DocVQA, ChartQA, and ChartQA-Pro into standardized JSONL formats.
📖 Paper: Describe Anything Model for Visual Question Answering on Text-rich Images⚠️ Note: Images not included - obtain from original sources with proper licensing
Repository Structure
DAM-QA-annotations/… See the full description on the dataset page: https://huggingface.co/datasets/VLAI-AIVN/DAM-QA-annotations.llm-delusion-response-annotations
LLM Delusion-Like Belief Reinforcement Annotations
This dataset contains human annotations of responses generated by conversational large language models (LLMs) to prompts expressing potentially delusion-like or reality-distorted beliefs.
The purpose of the dataset is to support evaluation of whether conversational LLM responses may unintentionally reinforce or strengthen delusion-like beliefs.
Dataset Files
Consensus Dataset… See the full description on the dataset page: https://huggingface.co/datasets/vennu95/llm-delusion-response-annotations.llm-delusion-response-annotations
LLM Delusion-Like Belief Reinforcement Annotations
This dataset contains human annotations of responses generated by conversational large language models (LLMs) to prompts expressing potentially delusion-like or reality-distorted beliefs.
The purpose of the dataset is to support evaluation of whether conversational LLM responses may unintentionally reinforce or strengthen delusion-like beliefs.
Dataset Files
Consensus Dataset… See the full description on the dataset page: https://huggingface.co/datasets/ManjuKrish/llm-delusion-response-annotations.semantic_annotation
Dataset Card for Dataset Name
The dataset aims to describe the entity that we can found in wikda.
Dataset Details
Dataset Description
Curated by: Jean petit
Language(s) (NLP): This dataset it can be use to do NLP task like question-ansewering, semantic annotation, entity generation
License: MIT
Uses
Direct Use
This dataset have used to fine tune LLM for semantic annotation task
[More Information Needed]
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/yvelos/semantic_annotation.