datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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/G4KMU/t2-ragbench.hle-gpt-oss-120b-no-python-260222
hle-gpt-oss-120b-no-python-260222
Deep research agent evaluation on rl-rag/hle_text_only (test split).
Results
Metric
Value
pass@4
47.9%
avg@4
26.6%
Trajectory accuracy
26.6% (2292/8632)
Questions
2158
Trajectories
8632 (4 per question)
Avg tool calls
14.5
Full conversations
❌
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domains
huggingface.co
Tool Usage… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/hle-gpt-oss-120b-no-python-260222.ragbench
RAGBench
Dataset Overview
RAGBEnch is a large-scale RAG benchmark dataset of 100k RAG examples.
It covers five unique industry-specific domains and various RAG task types.
RAGBench examples are sourced from industry corpora such as user manuals, making it particularly relevant for industry applications.
RAGBench comrises 12 sub-component datasets, each one split into train/validation/test splits
Usage
from datasets import load_dataset
# load… See the full description on the dataset page: https://huggingface.co/datasets/galileo-ai/ragbench.browsecomp-gpt-oss-120b-260222
browsecomp-gpt-oss-120b-260222
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@4
46.8%
avg@4
23.9%
Trajectory accuracy
23.9% (1211/5064)
Questions
1266
Trajectories
5064 (4 per question)
Avg tool calls
26.1
Full conversations
✅
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domains
huggingface.co
Tool Usage… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-gpt-oss-120b-260222.jeb-rag
JEB-Bench
Charging the Gate Rent: Measured-Energy Accounting for Adaptive Retrieval-Augmented Generation
⚠️ Status: under construction. Phase 0 (measurement validation) and Phase 1
(index construction) are landing now. The oracle matrix (bench/oracle/) is
populated in Phase 2 and this card will be revised when it is complete. Do not
cite numbers from this repository until the status line says complete.
What this is
The first public per-query × per-configuration… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/jeb-rag.rag_multilingual_training_negatives
How this dataset was made
We trained on chunks sourced from the documents in MADLAD-400 dataset that had been evaluated to contain a higher amount of educational information according to a state-of-the-art LLM.
We took chunks of size 250 tokens, 500 tokens, and 1000 tokens randomly for each document.
We then used these chunks to generate questions and answers based on this text using a state-of-the-art LLM.
Finally, we selected negatives for each chunk using the similarity from the… See the full description on the dataset page: https://huggingface.co/datasets/lightblue/rag_multilingual_training_negatives.browsecomp-no-scroll-gpt-oss-120b
browsecomp-no-scroll-gpt-oss-120b
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@4
46.0%
avg@4
22.9%
Trajectory accuracy
22.9% (1160/5064)
Questions
1266
Trajectories
5064 (4 per question)
Avg tool calls
27.0
Full conversations
❌
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domains
huggingface.co
Tool… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-no-scroll-gpt-oss-120b.ragdag-admission-v2-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-admission-v2-results.browsecomp-high-effort-gpt-oss-120b
browsecomp-high-effort-gpt-oss-120b
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@4
44.1%
avg@4
22.9%
Trajectory accuracy
22.9% (1158/5064)
Questions
1266
Trajectories
5064 (4 per question)
Avg tool calls
55.4
Full conversations
❌
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
100
Temperature
0.7
Blocked domains
huggingface.co
Tool… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-high-effort-gpt-oss-120b.browsecomp-qwen35-35b-a3b-think
browsecomp-qwen35-35b-a3b-think
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@4
43.0%
avg@4
24.8%
Trajectory accuracy
24.8% (1258/5064)
Questions
1266
Trajectories
5064 (4 per question)
Avg tool calls
41.1
Full conversations
❌
Model & Setup
Model
Qwen3.5-35B-A3B
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domains
huggingface.co
Tool… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-qwen35-35b-a3b-think.full-fold-the-rag-parquet-merged0222t2-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.hle-gpt-oss-120b-with-python-260222
hle-gpt-oss-120b-with-python-260222
Deep research agent evaluation on unknown.
Results
Metric
Value
pass@4
39.5%
avg@4
17.5%
Trajectory accuracy
17.4% (1860/10660)
Questions
1350
Trajectories
10660 (4 per question)
Avg tool calls
0.0
Full conversations
❌
Model & Setup
Model
unknown
Judge
gpt-4o
Max tool calls
50
Temperature
0.7
Blocked domainsNone
Tool Usage
Tool
Calls
%… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/hle-gpt-oss-120b-with-python-260222.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.browsecomp-high-effort-full-gpt-oss-120b
browsecomp-high-effort-full-gpt-oss-120b
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@1
20.9%
avg@1
20.9%
Trajectory accuracy
20.9% (264/1266)
Questions
1266
Trajectories
1266 (1 per question)
Avg tool calls
52.9
Full conversations
✅
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
100
Temperature
0.7
Blocked domains
huggingface.co… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-high-effort-full-gpt-oss-120b.rag-bench
Dataset card for RAG-BENCH
Data Summary
RAG-bench aims to provide results of many commonly used RAG datasets. All the results in this dataset are evaluated by the RAG evaluation tool Rageval, which could be easily reproduced with the tool.
Currently, we have provided the results of ASQA dataset,ELI5 dataset and HotPotQA dataset.
Data Instance
ASQA
{
"ambiguous_question":"Who is the original artist of sound of silence?",
"qa_pairs":[{… See the full description on the dataset page: https://huggingface.co/datasets/golaxy/rag-bench.rag-corpus-v1
Part of the SZL Holdings governed estate — claims are designed to carry checkable receipts. Verification proves integrity & origin, never accuracy or performance.
SZLHOLDINGS/rag-corpus-v1 — Agentic-RAG corpus + per-organ FAISS indexes
Doctrine v10/v11. Embedding model: BAAI/bge-base-en-v1.5 (768-dim).
Built by the agentic-RAG SHIP directive (390_AGENTIC_RAG_FAISS_PER_SPACE).
Contents
corpus.jsonl — 762 chunks, each ~512 tokens with… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/rag-corpus-v1.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.browsecomp-oss-env-high-effort-gpt-oss-120b
browsecomp-oss-env-high-effort-gpt-oss-120b
Deep research agent evaluation on data/browsecomp.jsonl (normal split).
Results
Metric
Value
pass@1
19.4%
avg@1
19.4%
Trajectory accuracy
19.4% (245/1266)
Questions
1266
Trajectories
1266 (1 per question)
Avg tool calls
52.5
Full conversations
✅
Model & Setup
Model
gpt-oss-120b
Judge
gpt-4o
Max tool calls
100
Temperature
0.7
Blocked domains
huggingface.co… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/browsecomp-oss-env-high-effort-gpt-oss-120b.medicalpark-rag
Medical Park Türkçe Sağlık Makaleleri — RAG Sistemi
Türkçe tıbbi makaleler üzerine kurulmuş, eşik (threshold) tabanlı bir Retrieval-Augmented Generation (RAG) altyapısı.
1. Veri Seti
Kaynak: umutertugrul/turkish-hospital-medical-articles (CC BY 4.0)
Veri seti içeriği: 14 farklı Türk hastane/sağlık kuruluşunun web sitesinden çekilmiş Türkçe tıbbi makaleler, her kuruluş ayrı bir .parquet dosyası olarak sunuluyor (toplam ~25.000 makale, 14 kaynak: Acıbadem… See the full description on the dataset page: https://huggingface.co/datasets/Toivo0/medicalpark-rag.trec-ragtime-2026
TREC RAGTIME 2026 — sentence and passage renderings
A sentence-level view of the TREC RAGTIME 2026 news collection,
with two English machine translations of every non-English sentence and the passage boundaries used
for retrieval. Derived from trec-ragtime/ragtime2.
Pipeline, experiment design, run configurations and reproduction steps:
github.com/jknafou/trec-ragtime-2026
What is in here
Config
Splits
Rows
Contents
sentences
eng, spa, rus, zho
88,719… See the full description on the dataset page: https://huggingface.co/datasets/jknafou/trec-ragtime-2026.ragtopia_oldRAG-Evaluation-Dataset-KO
Dataset Card for Reconstructed RAG Evaluation Dataset (KO)
Dataset Summary
본 데이터셋은 allganize/RAG-Evaluation-Dataset-KO를 기반으로 PDF 파일을 포함하도록 재구성한 한국어 평가 데이터셋입니다. 원본 데이터셋에서는 PDF 파일의 경로만 제공되어 수동으로 파일을 다운로드해야 하는 불편함이 있었고, 일부 PDF 파일의 경로가 유효하지 않은 문제를 보완하기 위해 PDF 파일을 포함한 데이터셋을 재구성하였습니다.
Supported Tasks and Leaderboards
RAG Evaluation: 본 데이터는 한국어 RAG 파이프라인에 대한 E2E Evaluation이 가능합니다.
Languages
The dataset is in Korean (ko).
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/datalama/RAG-Evaluation-Dataset-KO.rag_instruct_benchmark_tester
Dataset Card for RAG-Instruct-Benchmark-Tester
Dataset Summary
This is an updated benchmarking test dataset for "retrieval augmented generation" (RAG) use cases in the enterprise, especially for financial services, and legal. This test dataset includes 200 questions with context passages pulled from common 'retrieval scenarios', e.g., financial news, earnings releases,
contracts, invoices, technical articles, general news and short texts.
The questions are segmented… See the full description on the dataset page: https://huggingface.co/datasets/llmware/rag_instruct_benchmark_tester.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.t2-ragbench-splitsREAL-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.narrativeqa-rag
NarrativeQA RAG
Dataset for Retrieval-Augmented Generation (RAG) based on NarrativeQA.
Structure
Subset
Splits
Description
corpus
train (default)
Wikipedia plot summaries shared across all query splits
queries
train, dev, test
Reading comprehension questions
qrels
train, dev, test
Relevance judgments (query ↔ document)
answers
train, dev, test
Reference answers (longest annotated answer)
Dataset statistics
Split
Queries… See the full description on the dataset page: https://huggingface.co/datasets/DinoStackAI/narrativeqa-rag.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.
