datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LLM-Hallucination-Detection-complex-mathematics
AIME Hallucination Detection Dataset
This dataset is created for detecting hallucinations in Large Language Models (LLMs), particularly focusing on complex mathematical problems. It can be used for tasks like model evaluation, fine-tuning, and research.
Dataset Details
Name: AIME Hallucination Detection Dataset
Format: CSV
Size: (add size, e.g., 10MB)
Files Included:
AIME-hallucination-detection-dataset.csv: Contains the dataset.
Content Description… See the full description on the dataset page: https://huggingface.co/datasets/tourist800/LLM-Hallucination-Detection-complex-mathematics.rag-hallucination-benchmark
RAG Hallucination Benchmark
Context
Retrieval-Augmented Generation (RAG) is the industry standard for reducing LLM hallucinations, but detecting when a RAG system fails is a massive challenge. Most existing benchmarks focus only on massive Deep Learning models and lack tabular features.
This dataset provides a clean, engineered setup to train models (from XGBoost to RoBERTa) to detect hallucinations, predict context faithfulness, and measure answer relevance.… See the full description on the dataset page: https://huggingface.co/datasets/vkshdev/rag-hallucination-benchmark.AIME_Hallucination_Detection
AIME Hallucination Detection Dataset
This dataset is created for detecting hallucinations in Large Language Models (LLMs), particularly focusing on complex mathematical problems. It can be used for tasks like model evaluation, fine-tuning, and research.
Dataset Details
Name: AIME Hallucination Detection Dataset
Format: CSV
Size: (14.6 MB)
Files Included:
AIME-hallucination-detection-dataset.csv: Contains the dataset.
Content Description
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/tourist800/AIME_Hallucination_Detection.Language-Vision-Hallucinations
Dataset for Techen Project 095280
A comprehensive dataset for the Techen Project, focused on examining hallucinations in multi-modal AI-generated text by investigating model uncertainty, text generation patterns, and linguistic factors.
Columns Overview
image_link: URL to the image associated with each data row.
temperature: Temperature setting for text generation, controlling output randomness.
description: Text generated by the model for each image, using the… See the full description on the dataset page: https://huggingface.co/datasets/wrom/Language-Vision-Hallucinations.ai-5node-infer-buf-lag-cpl-hallucination-propagation-v0.1
What this repo does
This dataset models hallucination propagation in agent ecosystems. It detects when inference pressure, weakened verification buffer, governance lag in review, and tight coupling through shared knowledge and automation cross the five-node cascade threshold into an unrecoverable hallucination propagation cascade.
This dataset models a five-node cascade: four interacting instability drivers and one emergent cascade state.The fifth node represents the nonlinear… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-5node-infer-buf-lag-cpl-hallucination-propagation-v0.1.hallucination_evaluationllm_hallucinationsclinical-quad-prior-text-context-window-loss-new-data-summary-extension-hallucination-v0.1What this repo does
This dataset models hallucinated narrative continuation in clinical summaries. It predicts when the interaction between prior text similarity, context window loss, lack of new data, and high summary extension rate indicates that new narrative content has been generated without supporting evidence.
Core quad
prior_text_similarity_index
context_window_loss_index
new_data_presence_index
summary_extension_rate_index
Prediction target
label_hallucinated_continuation
Row… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-prior-text-context-window-loss-new-data-summary-extension-hallucination-v0.1.algozee_rag-based-hallucination-reduction-in-llms
RAG-Based Hallucination Reduction in LLMs
Introduction to Large Language Models and Hallucination Problem
Dataset Info
Source: Kaggle
Original Size: 0.17 MB
Kaggle Downloads: 43
Files: 1
Files
llm_rag_dataset_6k.csv.csv
Mirrored from Kaggle
