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Table · dataset · 2026

MINTQA

Listed in Hugging Face Datasets

Description

MINTQA: A Multi-Hop Question Answering Benchmark for Evaluating LLMs on New and Tail Knowledge MINTQA evaluates how well LLMs answer complex multi-hop (1–4 hops) questions that involve unpopular and new knowledge. It has two subsets: Config Examples Dimension Per-hop type labels pop (MINTQA-POP) 17,887 Knowledge popularity: unpopular vs. popular facts R, F ti (MINTQA-TI) 10,479 Time: new facts (only in the 2024 Wikidata dump) vs. old facts (in both 2021 and 2024)… See the full description on the dataset page: huggingface.co/datasets/probejie/MINTQA.

Links

Where it is published

Documentation and papers

Catalogue records · 1

Topics

Stated by source
question answering · text
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsprobejie/MINTQA7 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:question-answeringsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0