datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rag_hallucinationsProvides examples of hallucinated responses for RAG applications.
groundtruth-hallucination-bench-sample
Groundtruth Data Hallucination Benchmark Sample
This public teaser contains 180 representative, source-backed examples from Groundtruth Data products.
Groundtruth Data builds verified evaluation, remediation, and held-out validation datasets for AI models using authoritative source data. The commercial workflow is:
Find where a model fails.
Prove the failure with a larger verified evaluation.
Provide targeted remediation/training data.
Validate improvement on untouched held-out… See the full description on the dataset page: https://huggingface.co/datasets/Groundtruth-Data/groundtruth-hallucination-bench-sample.hallucination-reduction-dpo-100k
Hallucination Reduction DPO (100K)
100,000 DPO preference pairs training LLMs to stay within knowledge bounds. The chosen response is accurate and appropriately uncertain; the rejected response is confident but wrong — fabricated statistics, fake citations, wrong facts, overclaimed certainty.
Motivation
Hallucination is the #1 reliability concern blocking enterprise LLM adoption. Models fail in predictable patterns:
Inventing specific statistics with false… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/hallucination-reduction-dpo-100k.hallucination-grounding-dpo-4k
Hallucination Grounding DPO Pairs (4K)
DPO preference pairs targeting the full spectrum of factuality failures — from hallucination to over-hedging.
Motivation
Existing refusal/safety datasets focus on what not to say. This dataset targets the orthogonal challenge: when to say "I don't know" vs. when to answer confidently. Models that over-refuse waste user trust; models that hallucinate destroy it.
Dataset Description
4,000 preference pairs across… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/hallucination-grounding-dpo-4k.RAGTruth-Hallucinations
ToolACE
ToolACE is an automatic agentic pipeline designed to generate Accurate, Complex, and divErse tool-learning data.
ToolACE leverages a novel self-evolution synthesis process to curate a comprehensive API pool of 26,507 diverse APIs.
Dialogs are further generated through the interplay among multiple agents, guided by a formalized thinking process.
To ensure data accuracy, we implement a dual-layer verification system combining rule-based and model-based checks.
More details… See the full description on the dataset page: https://huggingface.co/datasets/drond0174/RAGTruth-Hallucinations.