datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GridCorpus_9M_Sudoku_Puzzles_Enriched
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║ ▼… See the full description on the dataset page: https://huggingface.co/datasets/beta3/GridCorpus_9M_Sudoku_Puzzles_Enriched.puzzlescript-gists
PuzzleScript Human-Authored Games (Full Gist Corpus)
35,705 human-authored PuzzleScript games — the
complete source text of each — collected from public GitHub gists.
This is the full corpus: every distinct gist is kept, and each row is tagged
with its deduplication cluster so you can reduce to a unique set with a one-line
filter. The deduplication is reproducible from the shipped dedup_master.json +
dedup_master.py; non-vanilla PuzzleScript-Plus files are excluded (listed in… See the full description on the dataset page: https://huggingface.co/datasets/smearle/puzzlescript-gists.GLM-5.2-Logic-Puzzles
GLM-5.2 · Logical Puzzles
6000x traces distilled from GLM-5.2 on High reasoning
Token Count: 5M~?
Distribution:
Puzzles:
•Tokenization blindless ex: counting the r's in strawberry
•Goal reasoning ex: the car wash test (theres no car wash question exactly just prompts like it so its not just benchmaxxing)
•Reading comprehension traps
•Temporal reasoning
•Many other categories not worth mentioning
Prompts… See the full description on the dataset page: https://huggingface.co/datasets/ianncity/GLM-5.2-Logic-Puzzles.logic-grid-puzzles-training-pool
Logic grid puzzles training pool
Logic grid puzzles: a row of positions, a handful of attributes with one value per position, and a
list of clues that together admit exactly one arrangement. Two sets drawn for this pool by
generators run here under the seeds recorded below, and two public datasets read at the pinned
revisions named below, laid out twice. Train on either layer or on both.
pool.jsonl
Every source rewritten into one shape, 390945 rows, one JSON… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/logic-grid-puzzles-training-pool.zebra-puzzlesSynthetic data for the paper [2505.05755] Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions.
Project page: https://dhruveshp.com/projects/ilm
combi-puzzles
Combi-Puzzles Dataset
This repository contains the Combi-Puzzles dataset used in the research paper titled "Can Language Models Rival Mathematics Students? Evaluating Mathematical Reasoning through Textual Manipulation and Human Experiments." These variations are designed to evaluate problem-solving strategies across different formats.
Dataset Description
The Combi-Puzzles dataset includes 125 problems:
25 Base Combinatorial Problems: Covers permutations… See the full description on the dataset page: https://huggingface.co/datasets/andynik/combi-puzzles.rukh-puzzles-split
chorcat/rukh-puzzles-split
Lichess puzzles with rating deviation <= 100 and at least 100 plays, banded by difficulty (1000-1500, 1500-2000, 2000+) and split into test and train by a seeded hash of the puzzle id, each with the moves of the game it came from, for tactical evaluation and fine-tuning.
Part of Rukh, a chess language model built from scratch
as a course on generative and agentic AI. Every derived dataset ships with the exact filters and
counts of its manifest.json, so… See the full description on the dataset page: https://huggingface.co/datasets/chorcat/rukh-puzzles-split.knights-knaves-puzzles
Knights and Knaves Logic Puzzles Dataset
A comprehensive dataset of Knights and Knaves logic puzzles ranging from 3 to 14 inhabitants.
Each puzzle requires logical deduction to determine who tells the truth (knights) and who lies (knaves).
The dataset includes detailed chain-of-thought reasoning for each solution.
Dataset Description
This dataset contains 12,000 Knights and Knaves logic puzzles. In these puzzles:
Knights always tell the truth
Knaves always lie
The goal… See the full description on the dataset page: https://huggingface.co/datasets/RedaAlami/knights-knaves-puzzles.chess-debate-puzzles
Chess Debate Puzzles
A stratified sample of Lichess mid/endgame chess puzzles annotated with Stockfish-evaluated
moves across ten centipawn-quality bands. Designed for experiments in the spirit of
AI Safety via Debate (Irving et al., 2018), where two AI
agents argue for different moves and a judge must identify the objectively better one.
Motivation
Debate as an alignment technique asks whether a human (or AI) judge can identify the correct
answer when two agents argue… See the full description on the dataset page: https://huggingface.co/datasets/kvoudouris/chess-debate-puzzles.