dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
BCI Competition IV: ECoG to Finger Movements | #####Prediction of Finger Flexion IV Brain-Computer Interface Data Competition
The goal of this dataset is to predict the flexion of individual fingers from
signals recorded from the surface of the brain (electrocorticography (ECoG)). This data set contains
brain signals from three subjects, as well as the time co... | Provide a detailed description of the following dataset: BCI Competition IV: ECoG to Finger Movements |
Stanford ECoG library: ECoG to Finger Movements | Electrophysiological data from implanted electrodes in the human brain are rare, and therefore scientific access to it has remained somewhat exclusive. Here we present a freely-available curated library of implanted electrocorticographic (ECoG) data and analyses for 16 benchmark behavioral experiments, with 204 individ... | Provide a detailed description of the following dataset: Stanford ECoG library: ECoG to Finger Movements |
HuTu 80 | The image set contains 180 high-resolution color microscopic images of human duodenum adenocarcinoma HuTu 80 cell populations obtained in an in vitro scratch assay (for the details of the experimental protocol, we refer to (Liang et al., 2007)). Briefly, cells were seeded in 12-well culture plates ($20 \times 10^3$ cel... | Provide a detailed description of the following dataset: HuTu 80 |
CWL EEG/fMRI Dataset | EEG/fMRI Data from 8 subject doing a simple eyes open/eyes closed task is provided on this webpage.
The EEG/fMRI data are six files for each subject, with two basic factors: recording during Helium pump On and Helium pump Off, and recording during MRI scanning and without MRI scanning. In addition 'outside' EEG data... | Provide a detailed description of the following dataset: CWL EEG/fMRI Dataset |
SFpark | The San Francisco Municipal Transportation Agency (SFMTA) website provides data collected during the SFpark pilot project. On-street occupancy rate data contain per-block hourly occupancy rates and meter prices for seven parking districts. | Provide a detailed description of the following dataset: SFpark |
JRDB-Pose | **JRDB-Pose** is a large-scale dataset and benchmark for multi-person pose estimation and tracking using videos captured from a social navigation robot. The dataset contains challenge scenes with crowded indoor and outdoor locations and a diverse range of scales and occlusion types. It provides human pose annotations w... | Provide a detailed description of the following dataset: JRDB-Pose |
MGSM | Multilingual Grade School Math Benchmark (MGSM) is a benchmark of grade-school math problems. The same 250 problems from GSM8K are each translated via human annotators in 10 languages. GSM8K (Grade School Math 8K) is a dataset of 8.5K high-quality linguistically diverse grade school math word problems. The dataset was ... | Provide a detailed description of the following dataset: MGSM |
Demosthenes | Corpus for argument mining in legal documents, composed of 40 decisions of the Court of Justice of the European Union on matters of fiscal state aid | Provide a detailed description of the following dataset: Demosthenes |
FrenchMedMCQA | This paper introduces FrenchMedMCQA, the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain. It is composed of 3,105 questions taken from real exams of the French medical specialization diploma in pharmacy, mixing single and multiple answers. Each instance of the dat... | Provide a detailed description of the following dataset: FrenchMedMCQA |
High-cardinality Geometrically Shaped Constellation for the AWGN channel and optical fibre channel | Optimised constellation for the paper High-Cardinality Geometrical Constellation Shaping for the Nonlinear Fibre Channel. Each file is a constellation optimised for the SNR in dB mentioned in the filename, containing the coordinates of the constellation points as comma-separated values. Each column represents a dimensi... | Provide a detailed description of the following dataset: High-cardinality Geometrically Shaped Constellation for the AWGN channel and optical fibre channel |
CovidET | Crises such as the COVID-19 pandemic continuously threaten our world and emotionally affect billions of people worldwide in distinct ways. Understanding the triggers leading to people's emotions is of crucial importance. Social media posts can be a good source of such analysis, yet these texts tend to be charged with m... | Provide a detailed description of the following dataset: CovidET |
CrossRE | **CrossRE** is a cross-domain benchmark for Relation Extraction (RE), which comprises six distinct text domains and includes multi-label annotations. The dataset includes meta-data collected during annotation, to include explanations and flags of difficult instances. | Provide a detailed description of the following dataset: CrossRE |
ALTO | **ALTO** is a vision-focused dataset for the development and benchmarking of Visual Place Recognition and Localization methods for Unmanned Aerial Vehicles. The dataset is composed of two long (approximately 150km and 260km) trajectories flown by a helicopter over Ohio and Pennsylvania, and it includes high precision G... | Provide a detailed description of the following dataset: ALTO |
PAXRay | Projection of RibFrac CT dataset to a 2D plane to imitate X-Ray data for a total of 880 images with multi-label segmentation masks.
The dataset contains fine-grained 92 individual labels of anatomical structures, which, when including super-classes, lead to a total of 166 labels in both lateral
and frontal view. | Provide a detailed description of the following dataset: PAXRay |
DiSCQ | **DiSCQ** is a newly curated question dataset composed of 2,000+ questions paired with the snippets of text (triggers) that prompted each question. The questions are generated by medical experts from 100+ MIMIC-III discharge summaries. This dataset is released to facilitate further research into realistic clinical Ques... | Provide a detailed description of the following dataset: DiSCQ |
Avalon | **Avalon** is a benchmark for generalization in Reinforcement Learning (RL). The benchmark consists of a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards. Avalon is unique among existing RL benchmarks in that... | Provide a detailed description of the following dataset: Avalon |
PoseScript | **PoseScript** is a dataset that pairs a few thousand 3D human poses from AMASS with rich human-annotated descriptions of the body parts and their spatial relationships. This dataset is designed for the retrieval of relevant poses from large-scale datasets and synthetic pose generation, both based on a textual pose des... | Provide a detailed description of the following dataset: PoseScript |
Perception Test | Perception Test is a benchmark designed to evaluate the perception and reasoning skills of multimodal models. It introduces real-world videos designed to show perceptually interesting situations and defines multiple tasks that require understanding of memory, abstract patterns, physics, and semantics – across visual, a... | Provide a detailed description of the following dataset: Perception Test |
TFW: Annotated Thermal Faces in the Wild Dataset | Face detection and subsequent localization of facial landmarks are the primary steps in many face applications. Numerous algorithms and benchmark datasets have been introduced to develop robust models for the visible domain. However, varying conditions of illumination still pose challenging problems. In this regard, th... | Provide a detailed description of the following dataset: TFW: Annotated Thermal Faces in the Wild Dataset |
SF-TL54: A Thermal Facial Landmark Dataset with Visual Pairs | Facial landmark detection is a cornerstone in many facial analysis tasks such as face recognition, drowsiness detection, and facial expression recognition. Numerous methodologies were introduced to achieve accurate and efficient facial landmark localization in visual images. However, there are only several works that a... | Provide a detailed description of the following dataset: SF-TL54: A Thermal Facial Landmark Dataset with Visual Pairs |
MovieCLIP | MovieCLIP is a movie-centric taxonomy of 179 scene labels derived from movie scripts and auxiliary web-based video datasets designed for visual scene recognition. | Provide a detailed description of the following dataset: MovieCLIP |
XiaChuFang Recipe Corpus | XiaChuFang Recipe Corpus contains recipes are from 下厨房 (XiaChuFang), a popular Chinese recipe sharing website. The full recipe corpus contains 1,520,327 Chinese recipes. Among them, 1,242,206 recipes belong to 30,060 dishes. A dish has 41.3 recipes on average. | Provide a detailed description of the following dataset: XiaChuFang Recipe Corpus |
Motion Policy Networks | This dataset contains a large set (~3.2 Million) of high quality expert trajectories generated from a geometrically consist hybrid planner in a wide variety of environment (~575,000 environments). We created this dataset to explore the capabilities of neural networks to learn complex robotic motion, mimicking a traditi... | Provide a detailed description of the following dataset: Motion Policy Networks |
TEACh | Robots operating in human spaces must be able to engage in natural language interaction with people, both understanding and executing instructions, and using conversation to resolve ambiguity and recover from mistakes. To study this, we introduce TEACh, a dataset of over 3,000 human--human, interactive dialogues to com... | Provide a detailed description of the following dataset: TEACh |
SDN | Situated Dialogue Navigation (SDN) is a navigation benchmark of 183 trials with a total of 8415 utterances, around 18.7 hours of control streams, and 2.9 hours of trimmed audio. SDN is developed to evaluate the agent's ability to predict dialogue moves from humans as well as generate its own dialogue moves and physical... | Provide a detailed description of the following dataset: SDN |
Breaking Bad | **Breaking Bad** is a large-scale dataset of fractured objects. The dataset contains around 10k meshes from PartNet and Thingi10k. For each mesh, 20 fracture modes are pre-computed and then simulate 80 fractures from them, resulting in a total of 1M breakdown patterns. This dataset serves as a benchmark that enables th... | Provide a detailed description of the following dataset: Breaking Bad |
RTI Rwanda Drone Crop Types | RTI International (RTI) generated 2,611 labeled point locations representing 19 different land cover types, clustered in 5 distinct agroecological zones within Rwanda. These land cover types were reduced to three crop types (Banana, Maize, and Legume), two additional non-crop land cover types (Forest and Structure), an... | Provide a detailed description of the following dataset: RTI Rwanda Drone Crop Types |
Wikipedia Knowledge Graph dataset | Wikipedia is the largest and most read online free encyclopedia currently existing. As such, Wikipedia offers a large amount of data on all its own contents and interactions around them, as well as different types of open data sources. This makes Wikipedia a unique data source that can be analyzed with quantitative da... | Provide a detailed description of the following dataset: Wikipedia Knowledge Graph dataset |
MSU Video Frame Interpolation | This is a dataset for video frame interpolation task. The dataset contains the 1920×1080 videos in 240 FPS for videos captured with iPhone 11 and in 120 FPS for gaming content captured with OBS. | Provide a detailed description of the following dataset: MSU Video Frame Interpolation |
Cross-institution Male Pelvic Structures | The data set includes 589 T2-weighted images acquired from the same number of patients collected by seven studies, INDEX, the SmartTarget Biopsy Trial, PICTURE, TCIA Prostate3T, Promise12, TCIA ProstateDx (Diagnosis) and the Prostate MR Image Database. Further details are reported in the respective study references.
... | Provide a detailed description of the following dataset: Cross-institution Male Pelvic Structures |
The Reddit Climate Change Dataset | The Reddit Climate Change Dataset is a dataset of 620K Reddit posts and 4.6M comments - all mentions of the terms "climate" and "change" until 2022-09-01 across the entire Reddit social network.
Both were procured with [SocialGrep's export feature](https://socialgrep.com/exports?utm_source=paperswithcode&utm_medium=li... | Provide a detailed description of the following dataset: The Reddit Climate Change Dataset |
BioNLI | **BioNLI** is a dataset in biomedical natural language inference. This dataset contains abstracts from biomedical literature and mechanistic premises generated with nine different strategies. | Provide a detailed description of the following dataset: BioNLI |
VizWiz Answer Grounding | Source: [paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Grounding_Answers_for_Visual_Questions_Asked_by_Visually_Impaired_People_CVPR_2022_paper.pdf)
Visual Question Answering (VQA) is the task of returning the answer to a question about an image. While most VQA services only return a natural langua... | Provide a detailed description of the following dataset: VizWiz Answer Grounding |
DiffusionDB | **DiffusionDB** is a large-scale text-to-image prompt dataset. It contains 2 million images generated by Stable Diffusion using prompts and hyperparameters specified by real users. | Provide a detailed description of the following dataset: DiffusionDB |
RGZ EMU: Semantic Taxonomy | The data used in
- "Radio Galaxy Zoo EMU: Towards a Semantic Radio Galaxy Morphology Taxonomy" (Bowles et al. submitted)
- "A New Task: Deriving Semantic Class Targets for the Physical Sciences" (Bowles et al. 2022: https://arxiv.org/abs/2210.14760) accepted at the Fifth Workshop on Machine Learning and the Physical... | Provide a detailed description of the following dataset: RGZ EMU: Semantic Taxonomy |
DeepSportRadar-v1 | **DeepSportradar** is a benchmark suite of computer vision tasks, datasets and benchmarks for automated sport understanding. DeepSportradar currently supports four challenging tasks related to basketball: ball 3D localization, camera calibration, player instance segmentation and player re-identification. For each of th... | Provide a detailed description of the following dataset: DeepSportRadar-v1 |
InfantBooks | A dataset of books for very young children. | Provide a detailed description of the following dataset: InfantBooks |
Commonsense LAMA probes | Probes to evaluate commonsense in language models. | Provide a detailed description of the following dataset: Commonsense LAMA probes |
UML Classes With Specs | # Repository for UML-English data
This repository contains the data used for "Extraction of UML Class Diagrams from Natural Language Specification" (Yang et al. 2022)
## Getting the dataset
To get the entire dataset, you must download the release containing `dataset.tar.gz`.
## Structure of the dataset
* `da... | Provide a detailed description of the following dataset: UML Classes With Specs |
CBIS-DDSM | This CBIS-DDSM (Curated Breast Imaging Subset of DDSM) is an updated and standardized version of the Digital Database for Screening Mammography (DDSM) . The DDSM is a database of 2,620 scanned film mammography studies. It contains normal, benign, and malignant cases with verified pathology information. The scale of t... | Provide a detailed description of the following dataset: CBIS-DDSM |
Articulation GAN: Unsupervised modeling of articulatory learning | Checkpoints, generated EMA representations, audio outputs, and annotations for paper titled "Articulation GAN: Unsupervised modeling of articulatory learning" | Provide a detailed description of the following dataset: Articulation GAN: Unsupervised modeling of articulatory learning |
Panoramic Video Panoptic Segmentation Dataset | **Panoramic Video Panoptic Segmentation Dataset** is a large-scale dataset that offers high-quality panoptic segmentation labels for autonomous driving. The dataset has labels for 28 semantic categories and 2,860 temporal sequences that were captured by five cameras mounted on autonomous vehicles driving in three diffe... | Provide a detailed description of the following dataset: Panoramic Video Panoptic Segmentation Dataset |
CS1QA | **CS1QA** is a dataset for code-based question answering in the programming education domain. It consists of 9,237 question-answer pairs gathered from chat logs in an introductory programming class using Python, and 17,698 unannotated chat data with code. | Provide a detailed description of the following dataset: CS1QA |
Housekeep | **Housekeep** a benchmark to evaluate common sense reasoning in the home for embodied AI. In Housekeep, an embodied agent must tidy a house by rearranging misplaced objects without explicit instructions specifying which objects need to be rearranged. The dataset contains where humans typically place objects in tidy and... | Provide a detailed description of the following dataset: Housekeep |
CFC | **Caltech Fish Counting Dataset** (**CFC**) is a large-scale dataset for detecting, tracking, and counting fish in sonar videos. This dataset contains over 1,500 videos sourced from seven different sonar cameras. | Provide a detailed description of the following dataset: CFC |
QAMPARI | **QAMPARI** is an ODQA benchmark, where question answers are lists of entities, spread across many paragraphs. It was created by (a) generating questions with multiple answers from Wikipedia's knowledge graph and tables, (b) automatically pairing answers with supporting evidence in Wikipedia paragraphs, and (c) manuall... | Provide a detailed description of the following dataset: QAMPARI |
The Stack | **The Stack** contains over 3TB of permissively-licensed source code files covering 30 programming languages crawled from GitHub. The dataset was created as part of the BigCode Project, an open scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs). | Provide a detailed description of the following dataset: The Stack |
4D Temperature Monitoring | This Kaggle repository is still under construction (as of October 2022).
More updates and improvements are shortly incoming.
This dataset contains 250 examples of temperature field simulations in a shallow aquifer.
Temperature logs are an important tool in the geothermal industry.
Temperature measurements fro... | Provide a detailed description of the following dataset: 4D Temperature Monitoring |
bFFHQ | Gender-biased FFHQ dataset (bFFHQ) has age as a target label and gender as a correlated bias, and the images are from the FFHQ dataset. The images include the dominant number of young women (i.e., aged 10-29) and old men (i.e., aged 40-59) in the training data. | Provide a detailed description of the following dataset: bFFHQ |
Vehicle Claims | The code to create the dataset is available [here](https://github.com/ajaychawda58/UADAD/blob/main/Code/Notebooks/create_dataset.ipynb).
The dataset used in the paper is available on [github](https://github.com/ajaychawda58/UADAD/tree/main/data/vehicle_claims)
- `Maker` - *Categorical* - The brand of the vehicle.
... | Provide a detailed description of the following dataset: Vehicle Claims |
S-TEST | S-TEST is a benchmark for measuring the specificity of the language of pre-trained language models. | Provide a detailed description of the following dataset: S-TEST |
Open Relation Modeling | Given two entities, generating a coherent sentence describing the relation between them.
E.g., (data mining, database) => data mining is a process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. | Provide a detailed description of the following dataset: Open Relation Modeling |
LM Email Address Leakage | Are Large Pre-Trained Language Models Leaking Your Personal Information? We analyze whether Pre-Trained Language Models (PLMs) are prone to leaking personal information. Specifically, we query PLMs for email addresses with contexts of the email address or prompts containing the owner's name. | Provide a detailed description of the following dataset: LM Email Address Leakage |
ENTIGEN | **ENTIGEN** is a benchmark dataset to evaluate the change in image generations conditional on ethical interventions across three social axes -- gender, skin color, and culture. It contains 246 prompts based on an attribute set containing diverse professions, objects, and cultural scenarios. | Provide a detailed description of the following dataset: ENTIGEN |
arXivEdits | **arXivEdits** an annotated corpus of 751 full papers from arXiv with gold sentence alignment across their multiple versions of revision, as well as fine-grained span-level edits and their underlying intentions for 1,000 sentence pairs. This dataset is designed for studying the human revision process in the scientific ... | Provide a detailed description of the following dataset: arXivEdits |
CodeSyntax | **CodeSyntax** is a large-scale dataset of programs annotated with the syntactic relationships in their corresponding abstract syntax trees. It contains 18,701 code samples annotated with 1,342,050 relation edges in 43 relation types for Python, and 13,711 code samples annotated with 864,411 relation edges in 39 relati... | Provide a detailed description of the following dataset: CodeSyntax |
Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews | 6000 French user reviews from three applications on Google Play (Garmin Connect, Huawei Health, Samsung Health) are labelled manually. We selected four labels: rating, bug report, feature request and user experience.
* **Ratings** are simple text which express the overall evaluation to that app, including praise, cr... | Provide a detailed description of the following dataset: Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews |
TLMSDD | none | Provide a detailed description of the following dataset: TLMSDD |
PDEBench - Benchmark for Scientific Machine Learning | **PDEBench** provides a diverse and comprehensive set of benchmarks for scientific machine learning, including challenging and realistic physical problems. The repository consists of the code used to generate the datasets, to upload and download the datasets from the data repository, as well as to train and evaluate di... | Provide a detailed description of the following dataset: PDEBench - Benchmark for Scientific Machine Learning |
SDOML | Machine-learning Data Set Prepared from NASA Solar Dynamics Observatory Mission data.
* It contains data from 2010 to 2018 of the AIA and HMI instruments
* Multi-wavelength full-disk images of the solar corona
* about 7TB in total | Provide a detailed description of the following dataset: SDOML |
RaVAEn_21 | Annotated Earth Observation dataset of extreme events | Provide a detailed description of the following dataset: RaVAEn_21 |
GDSCv2 | We have characterised 1000 human cancer cell lines and screened them with 100s of compounds.
On this website, you will find drug response data and genomic markers of sensitivity.
The Genomics of Drug Sensitivity in Cancer Project - http://www.cancerrxgene.org/ - was part of a Wellcome Trust funded collaboration bet... | Provide a detailed description of the following dataset: GDSCv2 |
Tabula Sapiens | Human single-cell atlas. | Provide a detailed description of the following dataset: Tabula Sapiens |
Covid Assessment Centre Line Listing | A dataset that consists of the demographics, triage category, symptoms, and comorbidities of COVID-19 patients.
The dataset can be used to study the predictive factors of determining if a COVID-19 patient requires direct admission to the hospital. | Provide a detailed description of the following dataset: Covid Assessment Centre Line Listing |
Unpaired haze images | Unpaired dataset: The dataset is built by ourselves, and there are all real haze images from websites.
10000 images: Address：Baidu cloud disk Extraction code：zvh6
1000 images: Address：Baidu cloud disk Extraction code:47v9
Paired dataset: The dataset is added haze by ourselves according to the image... | Provide a detailed description of the following dataset: Unpaired haze images |
Lila | **Lila** is a unified mathematical reasoning benchmark consisting of 23 diverse tasks along four dimensions: (i) mathematical abilities e.g., arithmetic, calculus (ii) language format e.g., question-answering, fill-in-the-blanks (iii) language diversity e.g., no language, simple language (iv) external knowledge e.g., c... | Provide a detailed description of the following dataset: Lila |
QTautobase | Equilibrium structures of the tautobase(reference) optimized at the level of theory of popular quantum chemical databases (QM9,PC9 and ANI-E). The structures were generated from the SMILES structures of the original publication and then optimized using Gaussian09. For simplicity, structures are divided on type 'A' and ... | Provide a detailed description of the following dataset: QTautobase |
Meta-Album | Meta Album is a meta-dataset created for few-shot learning, meta-learning, continual learning and so on. Meta Album consists of 40 datasets from 10 unique domains. Datasets are arranged in sets (10 datasets, one dataset from each domain). It is a continuously growing meta-dataset.
We repurposed datasets that were ge... | Provide a detailed description of the following dataset: Meta-Album |
Parasitic Egg Detection and Classification in Microscopic Images | Parasitic infections have been recognized as one of the most significant causes of illnesses by WHO. Most infected persons shed cysts or eggs in their living environment, and unwittingly cause transmission of parasites to other individuals. Diagnosis of intestinal parasites is usually based on direct examination in the... | Provide a detailed description of the following dataset: Parasitic Egg Detection and Classification in Microscopic Images |
TUT Urban Acoustic Scenes 2018 | The dataset for this task is the TUT Urban Acoustic Scenes 2018 dataset, consisting of recordings from various acoustic scenes. The dataset was recorded in six large european cities, in different locations for each scene class. For each recording location there are 5-6 minutes of audio. The original recordings were spl... | Provide a detailed description of the following dataset: TUT Urban Acoustic Scenes 2018 |
TAU Audio-Visual Urban Scenes 2021 | The dataset for this task is TAU Audio-Visual Urban Scenes 2021. The dataset contains synchronized audio and video recordings from 12 European cities in 10 different scenes. | Provide a detailed description of the following dataset: TAU Audio-Visual Urban Scenes 2021 |
IGC | 111 | Provide a detailed description of the following dataset: IGC |
Financial Language Understanding Evaluation | **Financial Language Understanding Evaluation** is an open-source comprehensive suite of benchmarks for the financial domain. It contains benchmarks across 5 NLP tasks in financial domain as well as common benchmarks used in the previous research. The tasks are financial sentiment analysis, news headline classification... | Provide a detailed description of the following dataset: Financial Language Understanding Evaluation |
CausalBench | **CausalBench** is a comprehensive benchmark suite for evaluating network inference methods on large-scale perturbational single-cell gene expression data. CausalBench introduces several biologically meaningful performance metrics and operates on two large, curated and openly available benchmark data sets for evaluatin... | Provide a detailed description of the following dataset: CausalBench |
ACES | **ACES** a dataset consisting of 68 phenomena ranging from simple perturbations at the word/character level to more complex errors based on discourse and real-world knowledge. It can be used to evaluate a wide range of Machine Translation metrics. | Provide a detailed description of the following dataset: ACES |
Florence 4D | **Florence 4D** is a dataset that consists of dynamic sequences of 3D face models, where a combination of synthetic and real identities exhibit an unprecedented variety of 4D facial expressions, with variations that include the classical neutral-apex transition, but generalize to expression-to-expression. It is designe... | Provide a detailed description of the following dataset: Florence 4D |
bipedal-skills | The bipedal skills benchmark is a suite of reinforcement learning environments implemented for the MuJoCo physics simulator. It aims to provide a set of tasks that demand a variety of motor skills beyond locomotion, and is intended for evaluating skill discovery and hierarchical learning methods. The majority of tasks ... | Provide a detailed description of the following dataset: bipedal-skills |
E2E Refined | **E2E** Refined is a dataset for sentence classification. It consists of 40,560 examples for training, 4,489 for validation, and 4,555 for test. It is a refined version of the well-known MR-to-text
E2E dataset where many deletion/insertion/substitution errors has been fixed. | Provide a detailed description of the following dataset: E2E Refined |
Social Network Study | The SNS data (Valente et al., 2013) is a four-wave survey conducted in Los Angeles county, the
United States, which features a sample of 1,795 high-school students. The survey collected information about high-school students between grades 10 to 12, a majority of them self-identified as Hispanic. Among the collected i... | Provide a detailed description of the following dataset: Social Network Study |
YCB-Slide | The YCB-Slide dataset comprises of [DIGIT](https://digit.ml/) sliding interactions on [YCB](https://www.ycbbenchmarks.com) objects. We envision this can contribute towards efforts in tactile localization, mapping, object understanding, and learning dynamics models. We provide access to DIGIT images, sensor poses, RGB v... | Provide a detailed description of the following dataset: YCB-Slide |
Jonathan Benchimol | Source: [Text mining methodologies with R: An application to central bank texts](https://doi.org/10.1016/j.mlwa.2022.100286) | Provide a detailed description of the following dataset: Jonathan Benchimol |
KaggleDBQA | KaggleDBQA is a challenging cross-domain and complex evaluation dataset of real Web databases, with domain-specific data types, original formatting, and unrestricted questions.
It expands upon contemporary cross-domain text-to-SQL datasets in three key aspects:
(1) Its databases are pulled from real-world data sou... | Provide a detailed description of the following dataset: KaggleDBQA |
STAR: A Benchmark for Situated Reasoning in Real-World Videos | Reasoning in the real world is not divorced from situations. How to capture the present knowledge from surrounding situations and perform reasoning accordingly is crucial and challenging for machine intelligence. This paper introduces a new benchmark that evaluates the situated reasoning ability via situation abstracti... | Provide a detailed description of the following dataset: STAR: A Benchmark for Situated Reasoning in Real-World Videos |
LED Array Microscopy Frog Blood Dataset | Images collected on an LED array microscope (also known as a Fourier ptychographic microscope) on 172 fields-of-view of frog blood smears. Two of the fields-of-view ( example_000000 and example_000001) have 85 intensity images under single LED illumination, and all fields-of-view have 8 intensity images, 4 taken with u... | Provide a detailed description of the following dataset: LED Array Microscopy Frog Blood Dataset |
Cornell (60%/20%/20% random splits) | Node classification on Cornell with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Cornell (60%/20%/20% random splits) |
Film (60%/20%/20% random splits) | Node classification on Film with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Film (60%/20%/20% random splits) |
Squirrel (60%/20%/20% random splits) | Node classification on Squirrel with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Squirrel (60%/20%/20% random splits) |
PubMed (60%/20%/20% random splits) | Node classification on PubMed with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: PubMed (60%/20%/20% random splits) |
BAFMD | **BAFMD** contains images posted on Twitter during the pandemic from around the world with more images from underrepresented race and age groups to mitigate the problem for the face mask detection task. | Provide a detailed description of the following dataset: BAFMD |
Virtual-Pedcross-4667 | **Virtual-PedCross-4667** is a dataset for pedestrian crossing prediction. It consists of 4667 video sequences, 2862 pedestrian crossing sequences and 1804 not-crossing sequences. Totally, 745k video frames with the resolution of 1280×720 are saved. | Provide a detailed description of the following dataset: Virtual-Pedcross-4667 |
Title2Event | **Title2Event** is a large-scale sentence-level dataset for benchmarking Open Event Extraction without restricting event types. Title2Event contains more than 42,000 news titles in 34 topics collected from Chinese web pages. | Provide a detailed description of the following dataset: Title2Event |
ELPV | The dataset contains 2,624 samples of $300\times300$ pixels 8-bit grayscale images of functional and defective solar cells with varying degree of degradations extracted from 44 different solar modules. The defects in the annotated images are either of intrinsic or extrinsic type and are known to reduce the power effici... | Provide a detailed description of the following dataset: ELPV |
TripClick | TripClick is a large-scale dataset of click logs in the health domain, obtained from user interactions of the Trip Database health web search engine.
Provide:
* Approximately 5.2 million user interactions
* IR evaluation benchmark
* Trainin data for deep learning IR models | Provide a detailed description of the following dataset: TripClick |
Demonstration and Experience Replays | This is the data regarding the pre-generated demonstration and experience replay for the proposed Deep-GRAIL algorithm. You are welcomed to generate your own replays based on your problems at hand. | Provide a detailed description of the following dataset: Demonstration and Experience Replays |
Wisconsin(60%/20%/20% random splits) | Node classification on Wisconsin with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Wisconsin(60%/20%/20% random splits) |
Texas(60%/20%/20% random splits) | Node classification on Texas with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Texas(60%/20%/20% random splits) |
Chameleon(60%/20%/20% random splits) | Node classification on Chameleon with 60%/20%/20% random splits for training/validation/test. | Provide a detailed description of the following dataset: Chameleon(60%/20%/20% random splits) |
Deezer-Europe | Node classification on Deezer Europe with 50%/25%/25% random splits for training/validation/test. | Provide a detailed description of the following dataset: Deezer-Europe |
TransProteus | The dataset contains procedurally generated images of transparent vessels containing liquid and objects . The data for each image includes segmentation maps, 3d depth maps, and normal maps of of the liquid or object inside the transparent vessel, and the vessel. In addition, the properties of the materials inside the c... | Provide a detailed description of the following dataset: TransProteus |
PAGE | **PAGE** contains 98,525 games played by 2,007 professional players and spans over 70 years. The dataset includes rich AI analysis results for each move. | Provide a detailed description of the following dataset: PAGE |
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