datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DLR-Web
DLR-Web: Multidisciplinary Reasoning Dataset from Web Corpus [Project Page]
This repository releases the Design-Logic-Reasoning-Web (DLR-Web) dataset from the paper DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning (ICLR 2026).
Field definitions
original_document: web-sourced raw document text, further filtered from FineFineWeb; thanks to the FineFineWeb authors and maintainers for providing this resource
design_logic: Design Logic in… See the full description on the dataset page: https://huggingface.co/datasets/Attention1115/DLR-Web.quatiQuati ― Portuguese Native Information Retrieval dataset.DLLM-Planing-Task
DLLM-Planning-Task
Benchmark datasets for evaluating planning capabilities of Diffusion Language Models (DLLMs).
Dataset Description
This dataset contains multiple planning and combinatorial reasoning tasks designed to evaluate discrete diffusion language models. Each task has train/test splits in either CSV or JSONL format.
Tasks
Task
Format
Description
Sudoku
CSV
9x9 Sudoku puzzles. Columns: quizzes, solutions.
Path Finding (path-2-6)… See the full description on the dataset page: https://huggingface.co/datasets/zeyuzy/DLLM-Planing-Task.DL3DV-2k
DL3DV-2K
📖Paper
| 🏠Homepage
| 🤗ETCHR-FLUX.2-klein-9B Model
| 🤗ETCHR SFT-400K Dataset
| 🤗ETCHR GRPO-10K Dataset
| 🤗DL3DV-2K Benchmark
DL3DV-2K is a benchmark constructed from the DL3DV dataset for evaluating the viewpoint transformation capability of large models in spatial reasoning tasks, comprising 2K samples in total. Each sample contains: images (original images), aux_images (transformed images provided for human reference only and not used as question input)… See the full description on the dataset page: https://huggingface.co/datasets/internlm/DL3DV-2k.constitution-eval
ConstitutionEval
A blind, behavioral multiple-choice benchmark that measures whether a language model's
behavior aligns with a value constitution, without the constitution in context. Each item is a
realistic scenario ending at a decision point with four candidate courses of action; exactly one
is fully constitution-consistent and the other three each enact a specific, attractively-packaged
violation. A model scores well only if its internalised values match the constitution.… See the full description on the dataset page: https://huggingface.co/datasets/dlab-spp/constitution-eval.qa-ml-dl-jsonl
💡 AI Q&A Dataset for ML, DL, RL, TensorFlow, PyTorch
This dataset is designed to support training and evaluation of AI systems on question generation, answering, and understanding in the domains of Machine Learning, Deep Learning, Reinforcement Learning, TensorFlow, and PyTorch. It contains a large number of categorized questions along with high-quality answers in two different levels of brevity.
📁 Dataset Files
1. questions.jsonl
Lines: 24,510… See the full description on the dataset page: https://huggingface.co/datasets/Koushim/qa-ml-dl-jsonl.BESPOKE
BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback
Paper | Project Page | GitHub Repository
BESPOKE is a realistic benchmark specifically designed for evaluating personalization in search-augmented LLMs.
Data Fields
Query Table (queries/query_table.parquet)
Key
Type
Description
user
str
User identifier
query-id
str
Query identifier (canonical hyphen variant)
query
str
Natural-language query… See the full description on the dataset page: https://huggingface.co/datasets/yonsei-dli/BESPOKE.WenMind
WenMind Benchmark
NOTE this README was copied from https://github.com/SCUT-DLVCLab/WenMind/blob/main/README.md
2024/09/26 WenMind Benchmark paper has been accepted by NeurIPS 2024.
WenMind is a comprehensive benchmark dedicated for evaluating Large Language Models (LLMs) in Chinese Classical Literature and Language Arts (CCLLA). WenMind covers the sub-domains of Ancient Prose, Ancient Poetry, and Ancient Literary Culture, comprising 4,875 question-answer pairs, spanning 42… See the full description on the dataset page: https://huggingface.co/datasets/SCUT-DLVCLab/WenMind.dllm-qwen38-ar-baseline
AR baseline for the Qwen3.8-27B → block-diffusion conversion (GSM8K, pinned 500-problem subset)
日本語要約: Qwen/Qwen3.8-27B を Fast-dLLM v2 で
block-diffusion dLLM 化する計画の AR 参照スコアです。seed 固定の GSM8K 500 問・4-shot・
greedy で acc 0.968（484/500、skipped 0）。H100 1 枚で 42 分 ≈ $2.8。停止条件
（stop literal）として「block-diffusion 訓練 0.3B tokens の後、この subset で acc ≥ 0.918」
を要求し、届かなければ変換を続けません。訓練 run 自体はこの判断待ちで held です。
Why this exists — the stop literal
We are converting Qwen/Qwen3.8-27B into… See the full description on the dataset page: https://huggingface.co/datasets/com-junkawasaki/dllm-qwen38-ar-baseline.SAGEO-Arena
SAGEO Arena: A Realistic Environment for Evaluating Search-Augmented Generative Engine Optimization
SAGEO Arena is a benchmark for evaluating Search-Augmented Generative Engine Optimization (SAGEO) — the practice of optimizing web documents to improve their visibility in AI-generated responses.
Contents
This dataset releases the queries and Google Custom Search API results used to construct the SAGEO Arena corpus. Please follow the crawler instructions in the GitHub… See the full description on the dataset page: https://huggingface.co/datasets/yonsei-dli/SAGEO-Arena.dlgs_81_08_qaThis dataset contains an automatically generated set of Question and Answers extracted from the "TESTO UNICO SULLA SALUTE E SICUREZZA SUL LAVORO 81/08" document link
The data is extracted from the article directly and the set of QA are generated using OpenAI text-davinci-003
UltraGrain
UltraBeacon
UltraBeacon is a high-quality English question-answering dataset prepared by Dl26 for text-generation and chat-style model training.
The dataset is converted from TriviaQA into a consistent assistant format with prompt, response, and messages fields. It is intended for supervised fine-tuning of general assistant models that need strong question answering behavior.
Dataset Details
Property
Value
Dataset name
UltraBeacon
Developer
Dl26… See the full description on the dataset page: https://huggingface.co/datasets/Dl26/UltraGrain.clara-stage2-data
Clara Stage 2 Training Data
Training data for Clara Stage 2 (Compression Instruction Tuning).
Dataset Description
This dataset contains high-quality QA pairs with single documents for training Clara's decoder adapter to generate answers from compressed document representations.
Data Format
Each record contains:
question: The query/question
answer: Gold answer
docs: List containing 1 document
meta: Source description
metadata: Additional metadata (repo, scope… See the full description on the dataset page: https://huggingface.co/datasets/dl3239491/clara-stage2-data.dllm-prm-llada-eval-gsm8k
LLaDA-8B-Base PRM-Guided Evaluation (GSM8K)
PRM-Guided generation outputs on GSAI-ML/LLaDA-8B-Base, full GSM8K test (1,319 problems), K=8, 16 configurations: {bidir, causal} × branch_every {16, 32, 48, 64} × seeds {42, 43}.
Summary (sample std)
Method
n
mean ± std
LLaDA bidir PRM-Guided
8
0.3164 ± 0.0075
LLaDA causal PRM-Guided
8
0.2225 ± 0.0090
LLaDA Vanilla K=1
1
0.2077
Bidir-over-causal gap: +9.4 pp, 95% CI [+8.5, +10.3] pp.
Schema
{… See the full description on the dataset page: https://huggingface.co/datasets/AnonyRepo/dllm-prm-llada-eval-gsm8k.UltraBeacon
UltraBeacon
UltraBeacon is a high-quality English question-answering dataset prepared by Dl26 for text-generation and chat-style model training.
The dataset is converted from TriviaQA into a consistent assistant format with prompt, response, and messages fields. It is intended for supervised fine-tuning of general assistant models that need strong question answering behavior.
Dataset Details
Property
Value
Dataset name
UltraBeacon
Developer
Dl26… See the full description on the dataset page: https://huggingface.co/datasets/Dl26/UltraBeacon.UltraAtlas
UltraAtlas
UltraAtlas is a high-quality English question-answering dataset prepared by Dl26 for text-generation and chat-style model training.
The dataset is converted from SQuAD v2 into a consistent assistant format with prompt, response, and messages fields. It is intended for supervised fine-tuning of general assistant models that need strong question answering behavior.
Dataset Details
Property
Value
Dataset name
UltraAtlas
Developer
Dl26
Source… See the full description on the dataset page: https://huggingface.co/datasets/Dl26/UltraAtlas.clara-stage3-data
Clara Stage 3 Training Data
Training data for Clara Stage 3 (End-to-End Retrieval Training).
Dataset Description
This dataset contains QA pairs with multiple documents (1 positive + 4 distractors) for training Clara's end-to-end retrieval and generation capabilities.
Data Format
Each record contains:
question: The query/question
answer: Gold answer
docs: List of 5 documents (1 positive + 4 distractors)
pos_index: Index of the positive document in the docs… See the full description on the dataset page: https://huggingface.co/datasets/dl3239491/clara-stage3-data.neocortirrhea-lexicon
Dataset Card: Neocortirrhea Lexicon Entry
Summary
This dataset entry defines and contextualizes the psychological, neurological, and somatic neologism Neocortirrhea.
Dataset Structure
JSON Lines Representation (data.jsonl)
{
"term": "Neocortirrhea",
"part_of_speech": "noun",
"phonetic": "/ˌniː.oʊˌkɔːr.tɪˈriː.ə/",
"etymology": "Neocortex (higher-order cognitive processing) + -rrhea (Greek rhoia: abnormal/excessive flow or… See the full description on the dataset page: https://huggingface.co/datasets/dlewicki/neocortirrhea-lexicon.dl_project_uncleaned