datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
scifact
SciFact
An MTEB dataset
Massive Text Embedding Benchmark
SciFact verifies scientific claims using evidence from the research literature containing scientific paper abstracts.
Task category
t2t
Domains
Academic, Medical, Written
Reference
https://github.com/allenai/scifact
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["SciFact"])
evaluator = mteb.MTEB(task)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/scifact.benchmark-scifactscifact
SciFact
rus-scifactscifact-fa-v2scifact_openscifact-generated-queries
Dataset Card for BEIR Benchmark
Dataset Summary
BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS, Robust04
Argument Retrieval: Touche-2020, ArguAna
Duplicate Question Retrieval: Quora, CqaDupstack
Citation-Prediction: SCIDOCS
Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/scifact-generated-queries.beir-nl-scifact
Dataset Card for BEIR-NL Benchmark
Dataset Summary
BEIR-NL is a Dutch-translated version of the BEIR benchmark, a diverse and heterogeneous collection of datasets covering various domains from biomedical and financial texts to general web content. Our benchmark is integrated into the Massive Multilingual Text Embedding Benchmark (MMTEB).
BEIR-NL contains the following tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018… See the full description on the dataset page: https://huggingface.co/datasets/clips/beir-nl-scifact.scifact-trscifact-chat-format
SciFact (Chat-Format Preparation)
This dataset is a chat-format preparation of SciFact for supervised fine-tuning (SFT).
Format
This format is commonly referred to as:
chat-format SFT data
instruction-tuning conversations
OpenAI-style messages format
Included files
train.jsonl
validation.jsonl
stats.json
prepare_scifact_unsloth.py
Source
Base dataset: allenai/scifact
Original Dataset Highlights
Original dataset: allenai/scifact… See the full description on the dataset page: https://huggingface.co/datasets/ali5341/scifact-chat-format.scifacts-KALEscifact-fa
Dataset Summary
SciFact-Fa is a Persian (Farsi) dataset designed for the Retrieval task, with a focus on scientific fact verification. It is a translated version of the original English SciFact dataset used in the BEIR benchmark and is part of the FaMTEB (Farsi Massive Text Embedding Benchmark) under the BEIR-Fa collection.
Language(s): Persian (Farsi)
Task(s): Retrieval (Scientific Fact Verification, Evidence Retrieval)
Source: Translated from the English SciFact dataset using… See the full description on the dataset page: https://huggingface.co/datasets/MCINext/scifact-fa.scifact
SciFact
beir-he-scifact
BeIR-HE: SciFact (Hebrew)
Hebrew translation of the SciFact BeIR benchmark dataset.
Translated using gemini-3.1-flash-lite (Vertex AI batch) with LLM-as-a-judge quality gates.
Usage
from datasets import load_dataset
corpus = load_dataset("biunlp/beir-he-scifact", split="corpus")
queries = load_dataset("biunlp/beir-he-scifact", split="queries")
qrels = load_dataset("biunlp/beir-he-scifact", name="qrels", split="test")
gpl-scifactscifact-top-20-gen-queries
NFCorpus: 20 generated queries (BEIR Benchmark)
This HF dataset contains the top-20 synthetic queries generated for each passage in the above BEIR benchmark dataset.
DocT5query model used: BeIR/query-gen-msmarco-t5-base-v1
id (str): unique document id in NFCorpus in the BEIR benchmark (corpus.jsonl).
Questions generated: 20
Code used for generation: evaluate_anserini_docT5query_parallel.py
Below contains the old dataset card for the BEIR benchmark.
Dataset Card for BEIR… See the full description on the dataset page: https://huggingface.co/datasets/income/scifact-top-20-gen-queries.splade-scifact-train-retrievalsscifact-generated-queries
Dataset Card for BEIR Benchmark
Dataset Summary
BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS, Robust04
Argument Retrieval: Touche-2020, ArguAna
Duplicate Question Retrieval: Quora, CqaDupstack
Citation-Prediction: SCIDOCS
Tweet… See the full description on the dataset page: https://huggingface.co/datasets/ravenous150/scifact-generated-queries.scifact-tevatronscifact-hard-negatives
Dataset Card
Dataset Details
This dataset contains a set of candidate documents for second-stage re-ranking on scifact
(test split in BEIR). Those candidate documents are composed of hard negatives mined from
gtr-t5-xl as Stage 1 ranker
and ground-truth documents that are known to be relevant to the query. This is a release from our paper
Policy-Gradient Training of Language Models for Ranking, so
please cite it if using this dataset.
Direct Use
You can… See the full description on the dataset page: https://huggingface.co/datasets/NeuralPGRank/scifact-hard-negatives.splade-scifact-retrievalsscifact-corpus
SciFact Corpus
Scientific document retrieval corpus from the SciFact dataset.
Features
docid: document identifier
title: document title
text: document contents
trailrag-scifact-test