datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
olympiad_style_integer_math_problems
Olympiad Math Corpus
Version: v2.1.1
Release date: 2026-05-03
59,486 synthetically generated olympiad-style math problems with verified integer answers and formal computation graphs.
Loading
from datasets import load_dataset
ds = load_dataset("mihailgribov/olympiad_style_integer_math_problems", split="train")
lemma_applicability is stored as list[{lemma, status}] rather than a sparse dict (required for Arrow-based consumers). To convert to a dict for local use:… See the full description on the dataset page: https://huggingface.co/datasets/mihailgribov/olympiad_style_integer_math_problems.taocp_open_problems
TAOCP Open Problems
Collection of open research problems singled out by Donald Knuth in
The Art of Computer Programming series. Its main purpose is to help measure how frontier models understand, investigate, and make verifiable progress on hard but interesting open problems.
Contents
The dataset contains 9 exercises rated 50, M50, or HM50 in the six
TAOCP editions and draft bundles available to this project. Knuth uses these
ratings for problems that were not… See the full description on the dataset page: https://huggingface.co/datasets/sytelus/taocp_open_problems.aletheia_code_problems
Aletheia Code Problems with Misleading Hints
Dataset Description
This dataset contains multiple-choice code-reasoning problems derived from Aletheia-Bench and augmented with misleading textual hints. The misleading hints are intentionally designed to point to an incorrect answer.
The dataset was developed as part of the UnfaithRL project, which studies cue-following and unfaithful reasoning under reinforcement learning with verifiable rewards.
Specifically, it was… See the full description on the dataset page: https://huggingface.co/datasets/UnfaithRL/aletheia_code_problems.