mglockner/neoqa
NeoQA: Evidence-based Question Answering with Generated News Events NeoQA is a dataset for evaluating evidence-based question answering in language models. To avoid overlap with pretraining data, all questions and accompanying news articles are grounded in synthetically generated, fictional timelines of consecutive events, rather than real-world occurrences. This design enables a focused evaluation of a model’s evidence-based reasoning, independent of prior knowledge… See the full description on the dataset page: https://huggingface.co/datasets/mglockner/neoqa.
| Author / organization | mglockner |
|---|---|
| License (as declared) | cc-by-nd-4.0 |
| Downloads | 376 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 11 April 2025 |
| Last updated at source | 12 May 2025 |
Popularity, last 2 days
376 now (+28 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: NeoQA: Evidence-based Question Answering with Generated News Events NeoQA is a dataset for evaluating evidence-based question answering in language models. To avoid overlap with pretraining data, all questions and accompanying news articles → NeoQA: Evidence-based Question Answering with Generated News Events NeoQA is a dataset for evaluating evidence-based question answering in language models. To avoid overlap with pretraining data, all questions and accompanying news articles
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