dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
NLU++ | **nlu++** is a dataset for natural language understanding (NLU) in task-oriented dialogue (ToD) systems, with the aim to provide a much more challenging evaluation environment for dialogue NLU models, up to date with the current application and industry requirements. nlu++ is divided into two domains (banking and hotel... | Provide a detailed description of the following dataset: NLU++ |
FREDo | FREDo is a Few-Shot Document-Level Relation Extraction Benchmark based on DocRED and SciERC. The dataset is divided into four subsets: training set (62 relations), validation set (16 relations), in-domain test set (16 relations), and cross-domain test set (7 relations). | Provide a detailed description of the following dataset: FREDo |
SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions | Symlink is a SemEval shared task of extracting mathematical symbols and their descriptions from LaTeX source of scientific documents. This is a new task in SemEval 2022, which attracted 180 individual registrations and 59 final submissions from 7 participant teams. | Provide a detailed description of the following dataset: SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions |
OC-Cityscape | Out-of-Context Cityscapes (OC-Cityscapes) is a new dataset build
by replacing roads in the validation data of Cityscapes with various textures such as water, sand, grass, etc.
https://drive.google.com/file/d/1pKdlglcvsGseLzS1MX8SdjzQO2o1KZm6/view?usp=sharing | Provide a detailed description of the following dataset: OC-Cityscape |
ANUBIS | **ANUBIS** is a large-scale human skeleton dataset containing 80 actions. Compared with previously collected datasets, ANUBIS is advantageous in the following four aspects: (1) employing more recently released sensors; (2) containing novel back view; (3) encouraging high enthusiasm of subjects; (4) including actions of... | Provide a detailed description of the following dataset: ANUBIS |
Kompetencer | Kompetencer (en: competences) is a Danish job posting dataset annotated for nested spans of competences. | Provide a detailed description of the following dataset: Kompetencer |
ExVo2022 | Baseline code for the three tracks of ExVo 2022 competition.
Consists of 59,201 recordings totaling more than 36 hours of audio data from 1 702 speakers. To our knowledge, this is substantially larger than than any previously available dataset of human vocal bursts. | Provide a detailed description of the following dataset: ExVo2022 |
Cross-View Cross-Scene Multi-View Crowd Counting Dataset | A large synthetic multi-camera crowd counting dataset with a large number of scenes and camera views to capture many possible variations, which avoids the difficulty of collecting and annotating such a large real dataset.
The dataset is generated using GCC-CL [50], which works as a
plug-in for the game “Grand Thef... | Provide a detailed description of the following dataset: Cross-View Cross-Scene Multi-View Crowd Counting Dataset |
HaVG | A dataset that contains the description of an image or a section within the image in Hausa and its equivalent in English. Hausa, a Chadic language, is a member of the Afro-Asiatic language family. It is estimated that about 100 to 150 million people speak the language, with more than 80 million indigenous speakers. T... | Provide a detailed description of the following dataset: HaVG |
Biographical | Biographical is a semi-supervised dataset for RE. The dataset, which is aimed towards digital humanities (DH) and historical research, is automatically compiled by aligning sentences from Wikipedia articles with matching structured data from sources including Pantheon and Wikidata. | Provide a detailed description of the following dataset: Biographical |
ComPhy | ****Compositional Physical Reasoning** is a dataset for understanding object-centric and relational physics properties hidden from visual appearances. For a given set of objects, the dataset includes few videos of them moving and interacting under different initial conditions. The model is evaluated based on its capabi... | Provide a detailed description of the following dataset: ComPhy |
TuGebic | **TuGebic** is a corpus of recordings of spontaneous speech samples from Turkish-German bilinguals, and the compilation of a corpus called TuGebic. Participants in the study were adult Turkish and German bilinguals living in Germany or Turkey at the time of recording in the first half of the 1990s. The data were manual... | Provide a detailed description of the following dataset: TuGebic |
NHA12D | **NHA12D** is an annotated pavement crack dataset that contains images with different viewpoints and pavements types. This dataset is composed of 80 pavement images, including 40 concrete pavement images and 40 asphalt pavement images, captured by digital survey vehicles on the A12 network in the UK. | Provide a detailed description of the following dataset: NHA12D |
BigNews | Contains 3,689,229 English news articles on politics, gathered from 11 United States (US) media outlets covering a broad ideological spectrum. | Provide a detailed description of the following dataset: BigNews |
ORCAS-I | A labelled version of the ORCAS click-based dataset of Web queries, which provides 18 million connections to 10 million distinct queries.
DOI of the dataset: 10.48436/pp7xz-n9a06 | Provide a detailed description of the following dataset: ORCAS-I |
COUCH | **COUCH** is a large human-chair interaction dataset with clean annotations. The dataset consists of 3 hours and over 500 sequences of motion capture (MoCap) on human-chair interactions. | Provide a detailed description of the following dataset: COUCH |
ONCE-3DLanes | ONCE-3DLanes is a real-world autonomous driving dataset with lane layout annotation in 3D space. A dataset annotation pipeline is designed to automatically generate high-quality 3D lane locations from 2D lane annotations by exploiting the explicit relationship between point clouds and image pixels in 211,000 road scene... | Provide a detailed description of the following dataset: ONCE-3DLanes |
CareCall | **carecall** is a Korean dialogue dataset for role-satisfying dialogue systems. The dataset was composed with a few samples of human-written dialogues using in-context few-shot learning of large-scale LMs. Large-scale LMs can generate dialogues with a specific personality, given a prompt consisting of a brief descripti... | Provide a detailed description of the following dataset: CareCall |
VIS-TIR | A visible-light and thermal-infrared images dataset for dual-spectrum depth estimation. | Provide a detailed description of the following dataset: VIS-TIR |
TemporalWiki | TemporalWiki is a lifelong benchmark for ever-evolving LMs that utilizes the difference between consecutive snapshots of English Wikipedia and English Wikidata for training and evaluation, respectively. The benchmark hence allows researchers to periodically track an LM's ability to retain previous knowledge and acquire... | Provide a detailed description of the following dataset: TemporalWiki |
Charlotte-ThermalFace | **Charlotte-ThermalFace** is a thermal face dataset. The data is fully annotated with the facial landmarks, ambient temperature, relative humidity, the air speed of the room, distance to the camera, and subject thermal sensation at the time of capturing each image.
There are approximately 10,000 infrared thermal ima... | Provide a detailed description of the following dataset: Charlotte-ThermalFace |
ExaASC | The **ExaASC** dataset is a dataset for Target-based Stance Detection in the Arabic Language that contains different types of targets like persons, entities and events. This corpus contains about 9500 tweets with replies and target specified in the source tweet. Each sample has at least two stance annotations provided ... | Provide a detailed description of the following dataset: ExaASC |
Endomapper | The Endomapper dataset is the first collection of complete endoscopy sequences acquired during regular medical practice, including slow and careful screening explorations, making secondary use of medical data. Its original purpose is to facilitate the development and evaluation of VSLAM (Visual Simultaneous Localizatio... | Provide a detailed description of the following dataset: Endomapper |
BS-RSC | BS-RSC is a real-world rolling shutter (RS) correction dataset and a corresponding model to correct the RS frames in a distorted video. Real distorted videos with corresponding ground truth are recorded simultaneously via a well-designed beam-splitter-based acquisition system. BSRSC contains various motions of both cam... | Provide a detailed description of the following dataset: BS-RSC |
CAVES | **CAVES** is the first large-scale dataset containing about 10k COVID-19 anti-vaccine tweets labelled into various specific anti-vaccine concerns in a multi-label setting. This is also the first multi-label classification dataset that provides explanations for each of the labels. Additionally, the dataset also provides... | Provide a detailed description of the following dataset: CAVES |
D3 | DBLP is the largest open-access repository of scientific articles on computer science and provides metadata associated with publications, authors, and venues. We retrieved more than 6 million publications from DBLP and extracted pertinent metadata (e.g., abstracts, author affiliations, citations) from the publication t... | Provide a detailed description of the following dataset: D3 |
WikiWiki | **WikiWiki** is a dataset for understanding entities and their place in a taxonomy of knowledge—their types. It consists of entities and passages from 10M Wikipedia articles linked to the Wikidata knowledge graph with 41K types. | Provide a detailed description of the following dataset: WikiWiki |
ARCTIC | ARCTIC is a dataset of free-form interactions of hands and articulated objects. ARCTIC has 1.2M images paired with accurate 3D meshes for both hands and for objects that move and deform over time. The dataset also provides hand-object contact information. | Provide a detailed description of the following dataset: ARCTIC |
MeSHup | Contains 1,342,667 full text articles in English, together with the associated MeSH labels and metadata, authors, and publication venues that are collected from the MEDLINE database. | Provide a detailed description of the following dataset: MeSHup |
M-Phasis | A corpus of 9k German and French user comments collected from migration-related news articles. It goes beyond the hate-neutral dichotomy and is instead annotated with 23 features, which in combination become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of h... | Provide a detailed description of the following dataset: M-Phasis |
W-Oops | W-Oops consists of 2,100 unintentional human action videos, with 44 goal-directed and 30 unintentional video-level activity labels collected through human annotations. | Provide a detailed description of the following dataset: W-Oops |
SkillSpan | **SkillSpan** is a dataset for Skill Extraction (SE). It is an important and widely-studied task useful to gain insights into labor market dynamics. However, there is a lacuna of datasets and annotation guidelines; available datasets are few and contain crowd-sourced labels on the span-level or labels from a predefined... | Provide a detailed description of the following dataset: SkillSpan |
CoVERT | CoVERT is a fact-checked corpus of tweets with a focus on the domain of biomedicine and COVID-19-related (mis)information. The corpus consists of 300 tweets, each annotated with medical named entities and relations. Employs a novel crowdsourcing methodology to annotate all tweets with fact-checking labels and supportin... | Provide a detailed description of the following dataset: CoVERT |
Monant Medical Misinformation | This dataset of medical misinformation was collected and is published by Kempelen Institute of Intelligent Technologies (KInIT). It consists of approx. 317k news articles and blog posts on medical topics published between January 1, 1998 and February 1, 2022 from a total of 207 reliable and unreliable sources. The data... | Provide a detailed description of the following dataset: Monant Medical Misinformation |
StyleGAN-Human | A large-scale human image dataset with over 230K samples capturing diverse poses and textures. | Provide a detailed description of the following dataset: StyleGAN-Human |
Two4Two | Two4Two is a library to create synthetic image data crafted for human evaluations of interpretable ML approaches (esp. image classification). The synthetic images show two abstract animals: Peaky (arms inwards) and Stretchy (arms outwards). They are similar-looking, abstract animals, made of eight blocks. The core func... | Provide a detailed description of the following dataset: Two4Two |
LitMind Dictionary | An open-source online generative dictionary that takes a word and context containing the word as input and automatically generates a definition as output. Incorporating state-of-the-art definition generation models, it supports not only Chinese and English, but also Chinese-English cross-lingual queries. Moreover, it h... | Provide a detailed description of the following dataset: LitMind Dictionary |
OpenImage-O | It is manually annotated, comes with a naturally diverse distribution, and has a large scale. It is built to overcome several shortcomings of existing OOD benchmarks. OpenImage-O is image-by-image filtered from the test set of OpenImage-V3, which has been collected from Flickr without a predefined list of class names o... | Provide a detailed description of the following dataset: OpenImage-O |
IPM NEL | This data is for the task of named entity recognition and linking/disambiguation over tweets. It comprises
the addition of an entity URI layer on top of an NER-annotated tweet dataset. The task is to detect entities
and then provide a correct link to them in DBpedia, thus disambiguating otherwise ambiguous entity sur... | Provide a detailed description of the following dataset: IPM NEL |
PANACEA | The peer-reviewed publication for this dataset has been presented in the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), and can be accessed here: https://arxiv.org/abs/2205.02596. Please cite this when using the dataset.
This dataset contains a heteroge... | Provide a detailed description of the following dataset: PANACEA |
Coding competition 2 | Dataset for machine learning based performance prediction in online coding competitions. | Provide a detailed description of the following dataset: Coding competition 2 |
Alphabet stock price | This dataset provides full historical daily stock price for Alphabet. There are 2 types of share class for Alphabet: GOOG and GOOGL. The two classes have very similar share price. This dataset is for GOOGL. This dataset is provided by Finsheet, a world-class provider of [Excel stock price](https://finsheet.io/) and [st... | Provide a detailed description of the following dataset: Alphabet stock price |
DCF Valuation template | This is the DCF template provided by ValueInvesting.io, a high performing [value investing](https://valueinvesting.io/) platform. Within this template, users also have access to other models such as Dividend Discount Model and Earnings Power Value. The focus of ValueInvesting.io is to provide accurate and reliable [int... | Provide a detailed description of the following dataset: DCF Valuation template |
CUHK Avenue | Avenue Dataset contains 16 training and 21 testing video clips. The videos are captured in CUHK campus avenue with 30652 (15328 training, 15324 testing) frames in total. | Provide a detailed description of the following dataset: CUHK Avenue |
UBnormal | UBnormal is a new supervised open-set benchmark composed of multiple virtual scenes for video anomaly detection. Unlike existing data sets, the data set introduces abnormal events annotated at the pixel level at training time, for the first time enabling the use of fully-supervised learning methods for abnormal event d... | Provide a detailed description of the following dataset: UBnormal |
DRACO20K | DRACO20K dataset is used for evaluating object canonicalization on methods that estimate a canonical frame from a monocular input image.
Provides:
1. Mixed Reality Multi-view RGB-D images rendered from ShapeNet objects
2. Camera poses
3. NOCS maps
4. Semantic 2D keypoints with visibility
5. Object-centric mask | Provide a detailed description of the following dataset: DRACO20K |
QLEVR | Synthetic datasets have successfully been used to probe visual question-answering datasets for their reasoning abilities. [CLEVR](/dataset/clevr), for example, tests a range of visual reasoning abilities. The questions in CLEVR focus on comparisons of shapes, colors, and sizes, numerical reasoning, and existence claims... | Provide a detailed description of the following dataset: QLEVR |
VocalSet | VocalSet is a a singing voice dataset consisting of 10.1 hours of monophonic recorded audio of professional singers demonstrating both standard and extended vocal techniques on all 5 vowels. Existing singing voice datasets aim to capture a focused subset of singing voice characteristics, and generally consist of just a... | Provide a detailed description of the following dataset: VocalSet |
ASAP | There are eight essay sets. Each of the sets of essays was generated from a single prompt. Selected essays range from an average length of 150 to 550 words per response. Some of the essays are dependent upon source information and others are not. All responses were written by students ranging in grade levels from Grade... | Provide a detailed description of the following dataset: ASAP |
CelebA+masks | The COVID-19 pandemic raises the problem of adapting face recognition systems to the new reality, where people may wear surgical masks to cover their noses and mouths. Traditional data sets (e.g., CelebA, CASIA-WebFace) used for training these systems were released before the pandemic, so they now seem unsuited due to ... | Provide a detailed description of the following dataset: CelebA+masks |
CASIA-WebFace+masks | The COVID-19 pandemic raises the problem of adapting face recognition systems to the new reality, where people may wear surgical masks to cover their noses and mouths. Traditional data sets (e.g., CelebA, CASIA-WebFace) used for training these systems were released before the pandemic, so they now seem unsuited due to ... | Provide a detailed description of the following dataset: CASIA-WebFace+masks |
VocalSound | VocalSound is a free dataset consisting of 21,024 crowdsourced recordings of laughter, sighs, coughs, throat clearing, sneezes, and sniffs from 3,365 unique subjects. The VocalSound dataset also contains meta-information such as speaker age, gender, native language, country, and health condition. | Provide a detailed description of the following dataset: VocalSound |
ReMASC | We introduce a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems. In contrast to prior efforts, the proposed database contains genuine and replayed recordings of voice commands obtained in realistic usage scenarios and using state-of-the-... | Provide a detailed description of the following dataset: ReMASC |
CLUES (Classifier Learning Using natural language ExplanationS) | **CLUES** is a benchmark for Classifier Learning Using natural language ExplanationS, consisting of a range of classification tasks over structured data along with natural language supervision in the form of explanations. CLUES consists of 36 real-world (CLUES-Real) and 144 synthetic (CLUES-Synthetic) classification ta... | Provide a detailed description of the following dataset: CLUES (Classifier Learning Using natural language ExplanationS) |
CVRPTW | Random sampled instances of the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) for 20, 50 and 100 customer nodes.
* Coordinates sampled from unit square
* demands sampled as integers from range [1, 9]
* time windows sampled with:
- ready times (TW start) as random integers in time horizon T
... | Provide a detailed description of the following dataset: CVRPTW |
QA2D | The Question to Declarative Sentence (QA2D) Dataset contains 86k question-answer pairs and their manual transformation into declarative sentences. 95% of question answer pairs come from SQuAD (Rajkupar et al., 2016) and the remaining 5% come from four other question answering datasets. | Provide a detailed description of the following dataset: QA2D |
FlickrLogos-32 | Object detection benchmark for logo detection.
Images are natural scenes. Each image contains multiple objects, and each image has a total of 1 logo. Logo detection & classification labels are provided. | Provide a detailed description of the following dataset: FlickrLogos-32 |
Nakdimon-test | Diacritized texts in Modern Hebrew, collected from eleven different sources.
Diacritized using Ktiv Male conventions. | Provide a detailed description of the following dataset: Nakdimon-test |
WebVidVQA3M | A dataset automatically generated using question generation neural models and alt-text video captions from the WebVid dataset, with 3M video-question-answer triplets. | Provide a detailed description of the following dataset: WebVidVQA3M |
NuScenes Occupancy Grids Dataset | Dynamic occupancy grids generated from NuScenes dataset. Dataset contains static environment and semantic labels, useful for long term prediction tasks. | Provide a detailed description of the following dataset: NuScenes Occupancy Grids Dataset |
OSCD | The Onera Satellite Change Detection dataset addresses the issue of detecting changes between satellite images from different dates.
It comprises 24 pairs of multispectral images taken from the Sentinel-2 satellites between 2015 and 2018. Locations are picked all over the world, in Brazil, USA, Europe, Middle-East a... | Provide a detailed description of the following dataset: OSCD |
Twitter US Airline Sentiment | A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service"). You can download the non-aggre... | Provide a detailed description of the following dataset: Twitter US Airline Sentiment |
State Traversal Observation Tokens | When arriving at each state, each observation token gets a coin toss to see whether it will appear in the output observation string. Numbers on the left are indices of observations, numbers on the right are indices of states. | Provide a detailed description of the following dataset: State Traversal Observation Tokens |
Twitter PoS VCB | The data is about 1.5 million English tweets annotated for part-of-speech using Ritter's extension of the PTB tagset. The tweets are from 2012 and 2013, tokenized using the GATE tokenizer and tagged jointly using the CMU ARK tagger and Ritter's T-POS tagger. Only when both these taggers' outputs are completely compatib... | Provide a detailed description of the following dataset: Twitter PoS VCB |
Ritter PoS | PTB-tagged English Tweets | Provide a detailed description of the following dataset: Ritter PoS |
zulu-stance | This is a stance detection dataset in the Zulu language. The data is translated to Zulu by Zulu native speakers, from English source texts.
Our paper aims at utilizing this progress made for English to transfers that knowledge into other languages, which is a non-trivial task due to the domain gap between English an... | Provide a detailed description of the following dataset: zulu-stance |
nordic_langid | Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. C... | Provide a detailed description of the following dataset: nordic_langid |
bornholmsk_parallel | This dataset is parallel text for Bornholmsk and Danish. | Provide a detailed description of the following dataset: bornholmsk_parallel |
bajer_danish_misogyny | This is a high-quality dataset of annotated posts sampled from social media posts and annotated for misogyny. Danish language. | Provide a detailed description of the following dataset: bajer_danish_misogyny |
SHAJ | This is an abusive/offensive language detection dataset for Albanian. The data is formatted following the OffensEval convention. Data is from Instagram and YouTube comments. | Provide a detailed description of the following dataset: SHAJ |
polstance | Political stance in Danish. Examples represent statements by politicians and are annotated for, against, or neutral to a given topic/article. | Provide a detailed description of the following dataset: polstance |
Animals-10 | It contains about 28K medium quality animal images belonging to 10 categories: dog, cat, horse, spyder, butterfly, chicken, sheep, cow, squirrel, and elephant.
All the images have been collected from "google images" and have been checked by humans. There is some erroneous data to simulate real conditions (eg. images... | Provide a detailed description of the following dataset: Animals-10 |
Pose Estimation Lunar Robot | ## Overview
**The goal:** using simulation data to train neural networks to estimate the pose of a rover's camera with respect to a known target object
**The mission context:**
A simulated lunar surface, with lunar landers and lunar rovers. To accomplish their ressource extraction mission, the rovers must dig, tra... | Provide a detailed description of the following dataset: Pose Estimation Lunar Robot |
CEREBRUM-7T | Ultra-high field MRI enables sub-millimetre resolution imaging of human brain, allowing to disentangle complex functional circuits across different cortical depths. Segmentation, meant as the partition of MR brain images in multiple anatomical classes, is an essential step in many functional and structural neuroimaging... | Provide a detailed description of the following dataset: CEREBRUM-7T |
RGB-Stacking | RGB-Stacking is a benchmark for vision-based robotic manipulation. The robot is trained to learn how to grasp objects and balance them on top of one another.
Image source: [https://github.com/deepmind/rgb_stacking](https://github.com/deepmind/rgb_stacking) | Provide a detailed description of the following dataset: RGB-Stacking |
FM WILN | This dataset was created while conducting the field report related to this paper. It includes 18.6 km of autonomous navigation in a boreal forest. The wintertime meteorological conditions are documented in the paper.
This dataset consists of various [ROSbags](http://wiki.ros.org/rosbag), including all data recorder... | Provide a detailed description of the following dataset: FM WILN |
Google Speech Commands - Musan | This noisy speech test set is created from the Google Speech Commands v2 [1] and the Musan dataset[2].
It could be downloaded here: https://zenodo.org/record/6066174#.Yn7NPJPMLyU
Specifically, we created this test set by mixing the speech in the Google Speech Commands v2 test set with random noise in the Musan d... | Provide a detailed description of the following dataset: Google Speech Commands - Musan |
MODA dataset | MODA is a large open-source dataset of high quality, human-scored sleep spindles (5342 spindles, from 180 subjects) that was produced by the Massive Online Data Annotation project. Sleep spindles were detected as a consensus of a number of human-expert scorers. With a median number of 5 experts scoring every EEG segmen... | Provide a detailed description of the following dataset: MODA dataset |
SuMe | Can language models read biomedical texts and explain the biomedical mechanisms discussed? In this work we introduce a biomedical mechanism summarization task. Biomedical studies often investigate the mechanisms behind how one entity (e.g., a protein or a chemical) affects another in a biological context. The abstracts... | Provide a detailed description of the following dataset: SuMe |
Echonet-Dynamic | Echocardiography, or cardiac ultrasound, is the most widely used and readily available imaging modality to assess cardiac function and structure. Combining portable instrumentation, rapid image acquisition, high temporal resolution, and without the risks of ionizing radiation, echocardiography is one of the most freque... | Provide a detailed description of the following dataset: Echonet-Dynamic |
CLAMS | Targeted syntactic evaluation datasets in 5 languages: English, French, German, Russian, and Hebrew. Data are translated from the targeted syntactic evaluation data of Marvin & Linzen (2018): https://aclanthology.org/D18-1151/ . All stimuli focus on subject-verb agreement. | Provide a detailed description of the following dataset: CLAMS |
SSVC | The Synthetic SVC (SSVC) dataset comprises 12,000 images with respective bounding box annotations and detailed graph representations. This dataset enables the development of
strong models for the interpretation of SVCs while skipping the time-consuming dense data annotation. | Provide a detailed description of the following dataset: SSVC |
Fire and Smoke Dataset | This dataset is collected by DataCluster Labs, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: [sales@datacluster.ai](mailto:sales@datacluster.ai)
This dataset is an extremely challenging set of over 7000+ original Fire and Smoke images captured ... | Provide a detailed description of the following dataset: Fire and Smoke Dataset |
CiteSum | CiteSum is a large-scale scientific extreme summarization benchmark. | Provide a detailed description of the following dataset: CiteSum |
Nakdimon-train | A collection of diacritized Hebrew text in a variety of registers and from different sources. | Provide a detailed description of the following dataset: Nakdimon-train |
FiNER-139 | FiNER-139 is comprised of 1.1M sentences annotated with eXtensive Business Reporting Language (XBRL) tags extracted from annual and quarterly reports of publicly-traded companies in the US. Unlike other entity extraction tasks, like named entity recognition (NER) or contract element extraction, which typically require ... | Provide a detailed description of the following dataset: FiNER-139 |
AVCAffe | We introduce AVCAffe, the first Audio-Visual dataset consisting of Cognitive load and Affect attributes. We record AVCAffe by simulating remote work scenarios over a video-conferencing platform, where subjects collaborate to complete a number of cognitively engaging tasks. AVCAffe is the largest originally collected (n... | Provide a detailed description of the following dataset: AVCAffe |
MAG-Scholar-C | MAG-Scholar-C is constructed by Bojchevski et al. based on Microsoft Academic Graph (MAG), in which nodes refer to papers, edges represent citation relations among papers and features are bag-of-words of paper abstracts. | Provide a detailed description of the following dataset: MAG-Scholar-C |
HeriGraph | The dataset contains constructed multi-modal features (visual and textual), pseudo-labels (on heritage values and attributes), and graph structures (with temporal, social, and spatial links) constructed using User-Generated Content data collected from Flickr social media platform in three global cities containing UNESC... | Provide a detailed description of the following dataset: HeriGraph |
Natural sentences that contain *any* | We scraped the Gutenberg Project and a subset of English Wikipedia to obtain the list of sentences that contain *any*. Next, using a combination of heuristics, we filtered the result with regular expressions to produce two sets of sentences (the second set underwent additional manual filtration):
* 3844 sentences w... | Provide a detailed description of the following dataset: Natural sentences that contain *any* |
Synthetic parallel sentences that contain *any* | We used the following procedure. First, we automatically identified the set of verbs and nouns to build our items from. To do so, we started with *bert-base-uncased* vocabulary. We ran all non-subword lexical tokens through a SpaCy POS. Further, we lemmatized the result using https://pypi.org/project/Pattern/ and dropp... | Provide a detailed description of the following dataset: Synthetic parallel sentences that contain *any* |
Simulated micro-Doppler Signatures | Simulated pulse Doppler radar signatures for four classes of helicopter-like targets. The classes differ in the number of rotating blades each kind of target carries, thus each class translates into a specific modulation pattern on the Doppler signature. Doppler signatures are a typical feature used to achieve radar ta... | Provide a detailed description of the following dataset: Simulated micro-Doppler Signatures |
Extended Minecraft Corpus dataset | Minecraft Corpus dataset with builder utterance annotations | Provide a detailed description of the following dataset: Extended Minecraft Corpus dataset |
E-KAR | The ability to recognize analogies is fundamental to human cognition. Existing benchmarks to test word analogy do not reveal the underneath process of analogical reasoning of neural models.
Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-of-its-kind Expla... | Provide a detailed description of the following dataset: E-KAR |
Replication Data for: Investigating the concentration of High Yield Investment Programs in the United Kingdom | The dataset provides information about 450 HYIPs collected between November 2020 and September 2021. This dataset was analyzed and the results are discussed in the paper. | Provide a detailed description of the following dataset: Replication Data for: Investigating the concentration of High Yield Investment Programs in the United Kingdom |
Domestic Trash / Garbage Dataset | ### **This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: [sales@datacluster.ai](mailto:sales@datacluster.ai)**
This dataset is an extremely challenging set of over 9000+ original Trash/Garbage images captured ... | Provide a detailed description of the following dataset: Domestic Trash / Garbage Dataset |
RTMV | **RTMV** is a large-scale synthetic dataset for novel view synthesis consisting of ∼300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resolution (1600 × 1600 pixels). The dataset is orders of magnitude larger than existing synthetic datasets for novel view synthesis, thus provi... | Provide a detailed description of the following dataset: RTMV |
Indian Traffic Sign Image Dataset | ### **This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: [sales@datacluster.ai](mailto:sales@datacluster.ai)**
This dataset is an extremely challenging set of over 2000+ original Indian Traffic Sign images cap... | Provide a detailed description of the following dataset: Indian Traffic Sign Image Dataset |
Jigsaw Toxic Comment Classification Dataset | You are provided with a large number of Wikipedia comments which have been labeled by human raters for toxic behavior. The types of toxicity are:
toxic
severe_toxic
obscene
threat
insult
identity_hate
You must create a model which predicts a probability of each type of toxicity for each comment.
File descri... | Provide a detailed description of the following dataset: Jigsaw Toxic Comment Classification Dataset |
Image Description Sequences | A dataset of description sequences, a sequence of expressions that together are meant to single out one image from an (imagined) set of other similar images. These sequences were produced in a monological setting, but with the instruction to imagine they were provided to a partner who successively asked for more inform... | Provide a detailed description of the following dataset: Image Description Sequences |
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