datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
formal_problem_solving_main
Dataset Card for Formal Problem-Solving Benchmarks
This dataset is part of the official implementation of Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving, accepted as an ICML 2026 Spotlight paper.
Links:
Paper: https://openreview.net/forum?id=hgMZraPlSv
Project: https://github.com/Purewhite2019/formal_problem_solving_main
Overview
The benchmark supports three evaluation settings:
Formal Problem-Solving (FPS): Given a… See the full description on the dataset page: https://huggingface.co/datasets/purewhite42/formal_problem_solving_main.problem_solving-reasoning-pashto-plus
Problem Solving & Reasoning Multilingual Dataset
This repository contains a specialized dataset focused on logical reasoning, problem-solving, and step-by-step cognitive workflows across multiple regional languages: Pashto (ps), Arabic (ar), Farsi (fa), Sindhi (sd), and Urdu (ur).
Dataset Overview
Languages: Pashto (پښتو), Arabic (العربية), Farsi (فارسی), Sindhi (سنڌي), Urdu (اردو)
Domain: Logical Reasoning, Problem Solving, Cognitive SFT
License: MIT… See the full description on the dataset page: https://huggingface.co/datasets/nassimjp/problem_solving-reasoning-pashto-plus.Reasoning_Problem_Solving_Dataset
Reasoning and Problem-Solving Dataset (RPSD)
Overview
The Reasoning and Problem-Solving Dataset (RPSD) is a comprehensive, high-quality set of synthetically generated question-answer pairs (150k+) tailored for training AI systems in logical reasoning and problem-solving. It spans multiple domains, including core reasoning techniques, specialized fields like science, mathematics, engineering, computer science, and philosophy, along with practical, real-world… See the full description on the dataset page: https://huggingface.co/datasets/mattwesney/Reasoning_Problem_Solving_Dataset.ToT_Reasoning_Problem_Solving_Dataset_V2
ToT-RPSD-V2
This dataset consists of 70,000 high-quality, synthetically generated Q&A pairs with a strong emphasis on reasoning (inspired by o1 type reasoning) and the use of "Train of Thought" methodologies. Each entry is meticulously structured into six key components: the question, answer, reasoning (detailing the thought process leading to the answer), a unique ID, topic tags, and a difficulty level. While the dataset strongly focuses on science and cognitive tasks, it… See the full description on the dataset page: https://huggingface.co/datasets/mattwesney/ToT_Reasoning_Problem_Solving_Dataset_V2.Creative-Problem-SolvingProblem-Solving-Reasoning