hallucination
resultsrequestsFinQA-hallucination-detection
FinQA Hallucination Detection
Dataset Summary
This dataset was created from a subset of the original FinQA dataset. For each user query (financial questions), we prompted an LLM to generate a response to this query based on provided context (financial statements and tables from the original FinQA).
Each generated LLM response is labeled based on whether it is correct or not. This dataset is thus useful for benchmarking reference-free LLM Eval and Hallucination… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/FinQA-hallucination-detection.hallucinations-dpowiki_bio_gpt3_hallucination
Dataset Card for WikiBio GPT-3 Hallucination Dataset
GitHub repository: https://github.com/potsawee/selfcheckgpt
Paper: SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
Dataset Summary
We generate Wikipedia-like passages using GPT-3 (text-davinci-003) using the prompt: This is a Wikipedia passage about {concept} where concept represents an individual from the WikiBio dataset.
We split the generated passages into… See the full description on the dataset page: https://huggingface.co/datasets/potsawee/wiki_bio_gpt3_hallucination.Whisper-Hallucination
Whisper Hallucination and Repetition Probes
This is a benchmark. Every evaluation config is test — do not fine-tune on it.
lexicon_synth is the exception: synthetic training material with its own train/test
split, and not one of the eight benchmark arms.
To build training data, exclude the items in
benchmark/exclusions.json
(546 FMA tracks, 1,168 FSD50K ids, 2,620 LibriSpeech utterances, the Malay stems). The
benchmark draws FSD50K eval and FMA shards 0–1, so training can use… See the full description on the dataset page: https://huggingface.co/datasets/Scicom-intl/Whisper-Hallucination.