datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
prop_logic_puzzleTemporal-Logic-Video-Dataset
Temporal Logic Video (TLV) Dataset
Temporal Logic Video (TLV) Dataset
Synthetic and real video dataset with temporal logic annotation
Explore the GitHub »
NSVS-TL Project Webpage
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NSVS-TL Source Code
Overview
The Temporal Logic Video (TLV) Dataset addresses the scarcity of state-of-the-art video datasets for long-horizon, temporally extended activity and object detection. It comprises two main components:
Synthetic… See the full description on the dataset page: https://huggingface.co/datasets/minkyuchoi/Temporal-Logic-Video-Dataset.logi_gluelsat_logic_games-analytical_reasoningNovel annotated evaluation dataset of LSAT logic games associated with paper:
Lost in the Logic: An Evaluation of Large Language Models’ Reasoning Capabilities on LSAT Logic Games
Arxiv: http://arxiv.org/pdf/2409.19012
If you find this dataset useful, please cite the paper!
@misc{malik2024lostlogicevaluationlarge,
title={Lost in the Logic: An Evaluation of Large Language Models' Reasoning Capabilities on LSAT Logic Games},
author={Saumya Malik},
year={2024}… See the full description on the dataset page: https://huggingface.co/datasets/saumyamalik/lsat_logic_games-analytical_reasoning.severity_ablation_logicGradients_Gradients_and_Text_Full_Logic_CaptionsLogicVistaLogicNLI
Dataset Card for "LogicNLI"
@inproceedings{tian-etal-2021-diagnosing,
title = "Diagnosing the First-Order Logical Reasoning Ability Through {L}ogic{NLI}",
author = "Tian, Jidong and
Li, Yitian and
Chen, Wenqing and
Xiao, Liqiang and
He, Hao and
Jin, Yaohui",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/LogicNLI.Chinese-Logic-Multiple-Choicelogical-fallacyhttps://github.com/causalNLP/logical-fallacy
@article{jin2022logical,
title={Logical fallacy detection},
author={Jin, Zhijing and Lalwani, Abhinav and Vaidhya, Tejas and Shen, Xiaoyu and Ding, Yiwen and Lyu, Zhiheng and Sachan, Mrinmaya and Mihalcea, Rada and Sch{\"o}lkopf, Bernhard},
journal={arXiv preprint arXiv:2202.13758},
year={2022}
}
logical-entailmenthttps://github.com/google-deepmind/logical-entailment-dataset
@inproceedings{
evans2018can,
title={Can Neural Networks Understand Logical Entailment?},
author={Richard Evans and David Saxton and David Amos and Pushmeet Kohli and Edward Grefenstette},
booktitle={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=SkZxCk-0Z},
}
SWE-Star
SWE-Star
Introduction
SWE-Star is a family of language models based on the Qwen2.5-Coder family and trained on the SWE-Star dataset. The dataset contains approximately 250k agentic coding trajectories distilled from Devstral-2-Small using SWE-Smith tasks.
The complete data generation, training, and evaluation pipeline is openly available in our GitHub repository, enabling anyone to reproduce our results.
Additional details are available in our blog posts.… See the full description on the dataset page: https://huggingface.co/datasets/LogicStar/SWE-Star.Logics-STEM-SFT-Dataset-Open-1.6M
Logics-STEM-SFT-Dataset-2.2M
📰 News
[2026.01.05]🔥 Release of our Techinical Report.
[2026.01.05]🔥 Release the first version of Logics-STEM-8B-SFT, Logics-STEM-8B-RL, /Logics-STEM-SFT-Dataset-Open-1.6M.
Overview
What is this dataset?
Logics-STEM-SFT-Dataset-2.2M is a curated long Chain-of-Thought (CoT) SFT dataset for STEM reasoning, built on top of high-quality open-source data and enhanced through a rigorous curation and distillation… See the full description on the dataset page: https://huggingface.co/datasets/Logics-MLLM/Logics-STEM-SFT-Dataset-Open-1.6M.multi-zebra-logic
Dataset Card for the MultiZebraLogic dataset
This dataset includes zebra puzzles in 39 European and 5 non-European languages and in two sizes: 2x3 and 4x5. It can be used for evaluating logical reasoning ability.
The data has been generated using the code in this repo.
Dataset Details
Dataset Description
Zebra puzzles are a type of constraint satisfaction problem. They describe a number of objects, N_objects, that each have attributes… See the full description on the dataset page: https://huggingface.co/datasets/alexandrainst/multi-zebra-logic.logical-reasoningLogical-Reasoning-1500-Datawizardlm8x22b-logical-math-coding-sft
自動生成したテキスト
WizardLM 8x22bで生成した論理・数学・コード系のデータです｡
一部の計算には東京工業大学のスーパーコンピュータTSUBAME4.0を利用しました｡
TroLL-Logic-Locking-based-Hardware-TrojansSWE-Smith
A extended version of the original SWE-smith-py dataset with more problem descriptions!
wizardlm8x22b-logical-math-coding-sft_additional
自動生成したテキスト
WizardLM 8x22bで生成した論理・数学・コード系のデータです｡
一部の計算には東京工業大学のスーパーコンピュータTSUBAME4.0を利用しました｡
Video-MME-v2-logic-only-replacedINSIDER_LLM_DETECTION_BENCHMARK
Insider LLM Detection Benchmark
Benchmark for detecting insider LLMs via double logging: the model's own action log is compared against an independent system log, and a discrepancy is the misalignment signal. The 18 scenarios and conditions are Anthropic's Agentic Misalignment grid, built verbatim from the framework's templates, which are bundled in this repo; the only change is a logging-instruction block appended to the system prompt. Companion code:… See the full description on the dataset page: https://huggingface.co/datasets/logicBombExe/INSIDER_LLM_DETECTION_BENCHMARK.LogicalReasoning-hard-v2logicnlg
LogicNLG Dataset
See the official wenhuchen/LogicNLG release on GitHub.
logical-reasoning-qa-dataset
Dataset Card for "logical-reasoning-qa-dataset"
More Information needed
first_rag_db_manuel_config_trial
Atlas Hospital Türkçe Medikal RAG Deneyi
Bu depo, bir metni parçalama, parçaları gömme (embedding), ChromaDB'ye kaydetme ve benzerlik eşiğiyle cevaplanabilirlik kararı verme adımlarını uçtan uca göstermek için hazırlanmış bir ödev çalışmasıdır.
Kaynak veri, umutertugrul/turkish-hospital-medical-articles veri setindeki Atlas Hospital bölümüdür. Ham dosyada 130 makale bulunur; metne göre yinelenen iki kayıt çıkarıldığında 128 benzersiz makale işlenir.
Bu çalışma eğitim amaçlıdır.… See the full description on the dataset page: https://huggingface.co/datasets/logicBombExe/first_rag_db_manuel_config_trial.LogicalReasoning-hard-v1LogicMark
LogicMark
A procedurally generated benchmark for evaluating symbolic logic in language models. Each problem presents a set of variable equality/inequality premises and asks the model to identify which conclusion necessarily follows.
Unlike knowledge-based benchmarks, LogicMark contains no facts a model could have memorised from pretraining. Every problem is generated fresh from abstract variable names (a, b, c, ...), so a model cannot pattern-match to training data - it must… See the full description on the dataset page: https://huggingface.co/datasets/AxiomicLabs/LogicMark.Logics-STEM-SFT-Dataset-Open-5.3MOmniParsingBench
🤗 Model | 📑 Technical Report | 💻 GitHub
OmniParsingBench is a comprehensive, large-scale, and high-quality evaluation corpus designed to rigorously evaluate the unified parsing capabilities of Multimodal Large Language Models (MLLMs) across diverse modalities.
Unlike traditional single-task benchmarks, OmniParsingBench assesses the full spectrum of parsing performance—from fundamental signal detection to complex semantic reasoning—across six primary domains: Document… See the full description on the dataset page: https://huggingface.co/datasets/Logics-MLLM/OmniParsingBench.