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20 dataset results for Fairness

Netflix Prize consists of about 100,000,000 ratings for 17,770 movies given by 480,189 users. Each rating in the training dataset consists of four entries: user, movie, date of grade, grade. Users and movies are represented with integer IDs, while ratings range from 1 to 5.

345 PAPERS • 1 BENCHMARK

UTKFace

The UTKFace dataset is a large-scale face dataset with long age span (range from 0 to 116 years old). The dataset consists of over 20,000 face images with annotations of age, gender, and ethnicity. The images cover large variation in pose, facial expression, illumination, occlusion, resolution, etc. This dataset could be used on a variety of tasks, e.g., face detection, age estimation, age progression/regression, landmark localization, etc.

202 PAPERS • 7 BENCHMARKS

MORPH

MORPH is a facial age estimation dataset, which contains 55,134 facial images of 13,617 subjects ranging from 16 to 77 years old.

169 PAPERS • 8 BENCHMARKS

FairFace

FairFace is a face image dataset which is race balanced. It contains 108,501 images from 7 different race groups: White, Black, Indian, East Asian, Southeast Asian, Middle Eastern, and Latino. Images were collected from the YFCC-100M Flickr dataset and labeled with race, gender, and age groups.

164 PAPERS • 1 BENCHMARK

WinoBias

WinoBias contains 3,160 sentences, split equally for development and test, created by researchers familiar with the project. Sentences were created to follow two prototypical templates but annotators were encouraged to come up with scenarios where entities could be interacting in plausible ways. Templates were selected to be challenging and designed to cover cases requiring semantics and syntax separately.

108 PAPERS • NO BENCHMARKS YET

RFW

RFW (Racial Faces in-the-Wild)

To validate the racial bias of four commercial APIs and four state-of-the-art (SOTA) algorithms.

60 PAPERS • NO BENCHMARKS YET

GVGAI (General Video Game AI)

The General Video Game AI (GVGAI) framework is widely used in research which features a corpus of over 100 single-player games and 60 two-player games. These are fairly small games, each focusing on specific mechanics or skills the players should be able to demonstrate, including clones of classic arcade games such as Space Invaders, puzzle games like Sokoban, adventure games like Zelda or game-theory problems such as the Iterative Prisoners Dilemma. All games are real-time and require players to make decisions in only 40ms at every game tick, although not all games explicitly reward or require fast reactions; in fact, some of the best game-playing approaches add up the time in the beginning of the game to run Breadth-First Search in puzzle games in order to find an accurate solution. However, given the large variety of games (many of which are stochastic and difficult to predict accurately), scoring systems and termination conditions, all unknown to the players, highly-adaptive genera

34 PAPERS • NO BENCHMARKS YET

HELP

The HELP dataset is an automatically created natural language inference (NLI) dataset that embodies the combination of lexical and logical inferences focusing on monotonicity (i.e., phrase replacement-based reasoning). The HELP (Ver.1.0) has 36K inference pairs consisting of upward monotone, downward monotone, non-monotone, conjunction, and disjunction.

28 PAPERS • 1 BENCHMARK

MIAP (More Inclusive Annotations for People)

MIAP is a dataset created by obtaining a new set of annotations on a subset of the Open Images dataset, containing bounding boxes and attributes for all of the people visible in those images, as the original Open Images dataset annotations are not exhaustive, with bounding boxes and attribute labels for only a subset of the classes in each image.

14 PAPERS • NO BENCHMARKS YET

DiveFace

A new face annotation dataset with balanced distribution between genders and ethnic origins.

10 PAPERS • 2 BENCHMARKS

ACS PUMS

ACS PUMS stands for American Community Survey (ACS) Public Use Microdata Sample (PUMS) and has been used to construct several tabular datasets for studying fairness in machine learning:

9 PAPERS • NO BENCHMARKS YET

SPEECH-COCO

SPEECH-COCO contains speech captions that are generated using text-to-speech (TTS) synthesis resulting in 616,767 spoken captions (more than 600h) paired with images.

9 PAPERS • NO BENCHMARKS YET

CI-MNIST (Correlated and Imbalanced MNIST) is a variant of MNIST dataset with introduced different types of correlations between attributes, dataset features, and an artificial eligibility criterion. For an input image $x$, the label $y \in \{1, 0\}$ indicates eligibility or ineligibility, respectively, given that $x$ is even or odd. The dataset defines the background colors as the protected or sensitive attribute $s \in \{0, 1\}$, where blue denotes the unprivileged group and red denotes the privileged group. The dataset was designed in order to evaluate bias-mitigation approaches in challenging setups and be capable of controlling different dataset configurations.

4 PAPERS • NO BENCHMARKS YET

DialogueFairness

The Dialogue Fairness dataset is used to evaluate and understand fairness in dialogue models, focusing on gender and racial biases.

2 PAPERS • NO BENCHMARKS YET

KANFace (KANFace Dataset)

KANFace consists of 40K still images and 44K sequences (14.5M video frames in total) captured in unconstrained, real-world conditions from 1,045 subjects. The dataset is manually annotated in terms of identity, exact age, gender and kinship.

2 PAPERS • 1 BENCHMARK

ICLR Database (ICLR Database (with Textual Covariates))

A maintained database tracks ICLR submissions and reviews, augmented with author profiles and higher-level textual features.

1 PAPER • NO BENCHMARKS YET

ImDrug

ImDrug is a comprehensive benchmark with an open-source Python library which consists of 4 imbalance settings, 11 AI-ready datasets, 54 learning tasks and 16 baseline algorithms tailored for imbalanced learning. It features modularized components including formulation of learning setting and tasks, dataset curation, standardized evaluation, and baseline algorithms. It also provides an accessible and customizable testbed for problems and solutions spanning a broad spectrum of the drug discovery pipeline such as molecular modeling, drug-target interaction and retrosynthesis.

1 PAPER • NO BENCHMARKS YET

default of credit card clients Data Set

This research aimed at the case of customers default payments in Taiwan and compares the predictive accuracy of probability of default among six data mining methods. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default will be more valuable than the binary result of classification - credible or not credible clients. Because the real probability of default is unknown, this study presented the novel Sorting Smoothing Method to estimate the real probability of default. With the real probability of default as the response variable (Y), and the predictive probability of default as the independent variable (X), the simple linear regression result (Y = A + BX) shows that the forecasting model produced by artificial neural network has the highest coefficient of determination; its regression intercept (A) is close to zero, and regression coefficient (B) to one. Therefore, among the six data mining techniques, artificial neural networ

1 PAPER • NO BENCHMARKS YET

ec-darkpattern

ec-darkpattern is a dataset for dark pattern detection and prepared its baseline detection performance with state-of-the-art machine learning methods. The original dataset was obtained from Mathur et al.’s study in 2019 [11kScale], which consists of 1,818 dark pattern texts from shopping sites. Negative samples, i.e., non-dark pattern texts, by retrieving texts from the same websites as Mathur et al.'s dataset.

1 PAPER • NO BENCHMARKS YET

fNIRS2MW (The Tufts fNIRS to Mental Workload Dataset)

The Tufts fNIRS to Mental Workload (fNIRS2MW) open-access dataset is a new dataset for building machine learning classifiers that can consume a short window (30 seconds) of multivariate fNIRS recordings and predict the mental workload intensity of the user during that window.

0 PAPER • NO BENCHMARKS YET

Datasets

20 dataset results for Fairness