datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
difficulty-aime_2025-generations
Generations Dataset: aime_2025
Paper: LLMs Encode Their Failures: Predicting Success from Pre-Generation ActivationsCode: GitHub
LLM-generated solutions across train/validation/test splits for multiple models.
Columns
Column
Type
Description
problem
str
Problem statement
generated_solutions
list
Generated solutions with scores
success_rate
float
Fraction of correct generations
majority_vote_is_correct
int (0/1)
Whether majority vote is correct
k… See the full description on the dataset page: https://huggingface.co/datasets/CoffeeGitta/difficulty-aime_2025-generations.Korean-DeepMath-with-Difficulty
Korean DeepMath with Difficulty
This dataset enriches ChuGyouk/Korean-DeepMath with difficulty and topic metadata from zwhe99/DeepMath-103K.
Join procedure
Rows are matched using Korean-DeepMath[extra_info][index] -> original DeepMath row index.
Added fields
original_index
difficulty
topic
Intended use
Prepared for controlled Korean mathematical reasoning SFT experiments, including difficulty-aware sampling such as TDCS.
No Easy /… See the full description on the dataset page: https://huggingface.co/datasets/Seungjun/Korean-DeepMath-with-Difficulty.japanese-math-empirical-difficulty-pilot-50k
Japanese Math Empirical Difficulty Pilot 50k
This dataset is a 50,000-problem empirical difficulty pilot, not a full empirical labeling of the original 5.66M-row source dataset.
It was created for LLM-jp experiment 0399, Team Victory SFT, to validate empirical difficulty label distribution, downstream split behavior, and the rollout/scoring pipeline before attempting labeling at the full 5.6M scale.
Current Status
This upload uses the v3 scorer with assistant-only… See the full description on the dataset page: https://huggingface.co/datasets/argo11/japanese-math-empirical-difficulty-pilot-50k.