datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
RAG_Evalt2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/G4KMU/t2-ragbench.BToks-vidore_rag_Infographic-VQA
BToks ViDoRe Infographic-VQA
This dataset repository contains Lance-format converted data used by the open-source reproduction code for Bottleneck Tokens for Unified Multimodal Retrieval (arXiv:2604.11095).
Source
Converted from vidore/colpali_train_set.
Subset/view: infographic_vqa. This repository does not change upstream ownership, licensing, citation requirements, or usage restrictions.
Format
The data is stored as Lance tables for the… See the full description on the dataset page: https://huggingface.co/datasets/siyrus/BToks-vidore_rag_Infographic-VQA.hle_text_onlyVDR_ibm-research_REAL-MM-RAG
VDR_ibm-research_REAL-MM-RAG - Overview
Dataset Summary
VDR_ibm-research_REAL-MM-RAG is a multimodal dataset that combines text and image data, and support tasks such as DSE retrieval (RAG).
Dataset Creation
This dataset is a merge and shuffle of the following datasets in the VDR format:
ibm-research/REAL-MM-RAG_TechSlides
ibm-research/REAL-MM-RAG_TechReport
ibm-research/REAL-MM-RAG_FinTabTrainSet
ibm-research/REAL-MM-RAG_FinTabTrainSet_rephrased… See the full description on the dataset page: https://huggingface.co/datasets/racineai/VDR_ibm-research_REAL-MM-RAG.nornikel-metallurgy-rag-index
Nornikel Metallurgy RAG Knowledge Base (для векторного индекса)
Дедуплицированный корпус текстовых фрагментов (и связанных изображений) из
технической базы знаний по металлургии/горному делу/обогащению — источник
для построения векторного индекса (Annoy) в пайплайне RAG.
Индекс НЕ включён в этот репозиторий — эмбеддинги и Annoy-индекс
строятся во время выполнения ноутбука Google Colab (на GPU, это быстрее,
чем на CPU), используя corpus.jsonl как исходные данные. Модель… See the full description on the dataset page: https://huggingface.co/datasets/brics-edtech/nornikel-metallurgy-rag-index.ragnacrimson
Bangumi Image Base of Ragna Crimson
This is the image base of bangumi Ragna Crimson, we detected 98 characters, 6899 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the… See the full description on the dataset page: https://huggingface.co/datasets/BangumiBase/ragnacrimson.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/botay/t2-ragbench.ragdag-results
RAGDAG results
Artefacts from RAGDAG - treating a multi-stage retrieval pipeline as a
structural causal model and computing path-specific effects exactly by freezing
stages, rather than estimating them.
Code: https://github.com/ValerianFourel/RAGDAG
Layout
One directory per collection, named after its ir_datasets id:
<dataset-tag>/
REPORT.md human-readable report incl. the PASS/FAIL verdict
MANIFEST.json provenance: git SHA, code… See the full description on the dataset page: https://huggingface.co/datasets/ValerianFourel/ragdag-results.vqa_plant-disease-classification-merged-datasetfashion-recommender-dataREAL-MM-RAG_FinReport
REAL-MM-RAG-Bench: A Real-World Multi-Modal Retrieval Benchmark
We introduced REAL-MM-RAG-Bench, a real-world multi-modal retrieval benchmark designed to evaluate retrieval models in reliable, challenging, and realistic settings. The benchmark was constructed using an automated pipeline, where queries were generated by a vision-language model (VLM), filtered by a large language model (LLM), and rephrased by an LLM to ensure high-quality retrieval evaluation. To simulate real-world… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinReport.REAL-MM-RAG_TechReport
REAL-MM-RAG-Bench: A Real-World Multi-Modal Retrieval Benchmark
We introduced REAL-MM-RAG-Bench, a real-world multi-modal retrieval benchmark designed to evaluate retrieval models in reliable, challenging, and realistic settings. The benchmark was constructed using an automated pipeline, where queries were generated by a vision-language model (VLM), filtered by a large language model (LLM), and rephrased by an LLM to ensure high-quality retrieval evaluation. To simulate real-world… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_TechReport.REAL-MM-RAG_TechSlides
REAL-MM-RAG-Bench: A Real-World Multi-Modal Retrieval Benchmark
We introduced REAL-MM-RAG-Bench, a real-world multi-modal retrieval benchmark designed to evaluate retrieval models in reliable, challenging, and realistic settings. The benchmark was constructed using an automated pipeline, where queries were generated by a vision-language model (VLM), filtered by a large language model (LLM), and rephrased by an LLM to ensure high-quality retrieval evaluation. To simulate real-world… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_TechSlides.indian-foods-dataset
Dataset Card for Indian Foods Dataset
Dataset Summary
This is a multi-category(multi-class classification) related Indian food dataset showcasing The-massive-Indian-Food-Dataset.
This card has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
English
Dataset Structure
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['biryani', 'cholebhature'… See the full description on the dataset page: https://huggingface.co/datasets/bharat-raghunathan/indian-foods-dataset.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/grasson/t2-ragbench.REAL-MM-RAG_TechSlides_BEIR
BEIR Version of REAL-MM-RAG_TechSlides
Summary
This dataset is the BEIR-compatible version of the following Hugging Face dataset:
ibm-research/REAL-MM-RAG_TechSlides
It has been reformatted into the BEIR structure for evaluation in retrieval settings.The original dataset is QA-style (each row is a query tied to a document image).Here, queries, qrels, docs, and corpus are separated into BEIR-standard splits.
REAL-MM-RAG_TechSlides
Content: 62 technical… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_TechSlides_BEIR.REAL-MM-RAG_FinReport_BEIR
BEIR Version of REAL-MM-RAG_FinReport
Summary
This dataset is the BEIR-compatible version of the following Hugging Face dataset:
ibm-research/REAL-MM-RAG_FinReport
It has been reformatted into the BEIR structure for evaluation in retrieval settings.The original dataset is QA-style (each row is a query tied to a document image).Here, queries, qrels, docs, and corpus are separated into BEIR-standard splits.
REAL-MM-RAG_FinReport
Content: 19 financial… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinReport_BEIR.REAL-MM-RAG_FinSlides_BEIR
BEIR Version of REAL-MM-RAG_FinSlides
Summary
This dataset is the BEIR-compatible version of the following Hugging Face dataset:
ibm-research/REAL-MM-RAG_FinSlides
It has been reformatted into the BEIR structure for evaluation in retrieval settings.The original dataset is QA-style (each row is a query tied to a document image).Here, queries, qrels, docs, and corpus are separated into BEIR-standard splits.
REAL-MM-RAG_FinSlides
Content: 65 quarterly… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinSlides_BEIR.clinical-skin-diseaseREAL-MM-RAG_TechReport_BEIR
BEIR Version of REAL-MM-RAG_TechReport
Summary
This dataset is the BEIR-compatible version of the following Hugging Face dataset:
ibm-research/REAL-MM-RAG_TechReport
It has been reformatted into the BEIR structure for evaluation in retrieval settings.The original dataset is QA-style (each row is a query tied to a document image).Here, queries, qrels, docs, and corpus are separated into BEIR-standard splits.
REAL-MM-RAG_TechReport
Content: 17 technical… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_TechReport_BEIR.agentic-rag-redteam-bench
WARNING: HARMFUL CONTENT - RESEARCH USE ONLY
This dataset contains adversarial prompts, jailbreak attacks, toxic outputs, and other explicitly harmful content generated for AI safety research. Samples include prompt injections, social engineering payloads, misinformation, hate speech, instructions for illegal activities, phishing templates, and other dangerous material. All content is synthetic and produced by automated red-teaming pipelines for the sole purpose of evaluating and improving… See the full description on the dataset page: https://huggingface.co/datasets/Fujitsu/agentic-rag-redteam-bench.REAL-MM-RAG_FinTabTrainSet
REAL-MM-RAG_FinTabTrainSet
We curated a table-focused finance dataset from FinTabNet (Zheng et al., 2021), extracting richly formatted tables from S&P 500 filings. We used an automated pipeline in which queries were generated by a vision-language model (VLM) and filtered by a large language model (LLM). We generated 48,000 natural-language (query, answer, page) triplets to improve retrieval models on table-intensive financial documents.
For more information, see the project page:… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinTabTrainSet.REAL-MM-RAG_FinSlides
REAL-MM-RAG-Bench: A Real-World Multi-Modal Retrieval Benchmark
We introduced REAL-MM-RAG-Bench, a real-world multi-modal retrieval benchmark designed to evaluate retrieval models in reliable, challenging, and realistic settings. The benchmark was constructed using an automated pipeline, where queries were generated by a vision-language model (VLM), filtered by a large language model (LLM), and rephrased by an LLM to ensure high-quality retrieval evaluation. To simulate real-world… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinSlides.multimodal-rag-indexREAL-MM-RAG_FinTabTrainSet_rephrased
REAL-MM-RAG_FinTabTrainSet_rephrased
We curated a table-focused finance dataset from FinTabNet (Zheng et al., 2021), extracting richly formatted tables from S&P 500 filings. We used an automated pipeline in which queries were generated by a vision-language model (VLM), filtered by a large language model (LLM), and rephrased by an LLM. We generated 48,000 natural-language (query, answer, page) triplets to improve retrieval models on table-intensive financial documents. This is the… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/REAL-MM-RAG_FinTabTrainSet_rephrased.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/tomsummerfield/t2-ragbench.ebr-rag-final-data-ingestclinical-skin-disease-imagesretail_visual_rag_pipeline
A Visual RAG Pipeline for Few-Shot Fine-Grained Product Classification
Paper
Accepted at The 12th Workshop on Fine-Grained Visual Categorization (FGVC12) at IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025.
Overview
The Retail Visual RAG Pipeline Dataset is a subset of the Retail-786k (Retail-786k) image dataset, supplemented with additional textual data per image.
Data
Image Data:
The images are cropped from scanned… See the full description on the dataset page: https://huggingface.co/datasets/blamm/retail_visual_rag_pipeline.