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Multiple-choice datasets
archive 2025-07-28
12 datasets carry the task tag "Multiple-choice" (the task itself: Multiple-choice), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Multiple-choice datasets 1–12 of 12
TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions.
607 papers · 3 benchmarks
MathVista (Mathematical Reasoning of in Visual Contexts)
MathVista is a consolidated Mathematical reasoning benchmark within Visual contexts.
242 papers · 0 benchmarks
Belebele is a multiple-choice machine reading comprehension (MRC) dataset spanning 122 language variants.
68 papers · 0 benchmarks
Math-Vision (Math-V) dataset is a meticulously curated collection of 3,040 high-quality mathematical problems with visual contexts sourced from real math competitions.
12 papers · 1 benchmark
Neptune (Neptune Long Video Understanding Benchmark)
Neptune is a dataset consisting of challenging question-answer-decoy (QAD) sets for long videos (up to 15 minutes).
12 papers · 0 benchmarks
We generate epistemic reasoning problems using modal logic to target theory of mind (tom) in natural language processing models.
4 papers · 0 benchmarks
Huggingface Datasets is a great library, but it lacks standardization, and datasets require preprocessing work to be used interchangeably.
3 papers · 0 benchmarks
MMInstruct-GPT4V (MMInstruct: A High-Quality Multi-Modal Instruction Tuning Dataset with Extensive Diversity)
Vision-language supervised fine-tuning effectively enhances VLLM performance, but existing visual instruction tuning datasets have limitations: 1.
1 paper · 0 benchmarks
Large Language Models (LLMs) have the potential to enhance Agent-Based Modeling by better representing complex interdependent cybersecurity systems, improving cybersecurity threat modeling and risk management.
1 paper · 0 benchmarks
This dataset tests the capabilities of language models to correctly capture the meaning of words denoting probabilities (WEP), e.g.
1 paper · 1 benchmark
TUMTraffic-VideoQA is a novel dataset designed to understand spatiotemporal video in complex roadside traffic scenarios.
1 paper · 0 benchmarks
Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.