13 datasets found

The e-SNLI dataset is a large-scale dataset for natural language inference, with human-written explanations for each sample.

Do models explain themselves? counterfactual simulatability of natural language explanations

A multilingual LLM for explaining and correcting translation errors

Fashionpedia-Taste is an explainable fashion taste dataset that challenges computer vision systems to predict whether a subject like a fashion image and provide explanations...

The Tweet Sentiment Extraction dataset contains positive, negative, and neutral tweets with human-annotated rationales.

The Movie Reviews dataset contains positive and negative movie reviews with rationales annotated by humans to support classification.

Challenge 3 - Blue and Yellow Circles: Set of all possible Kandinsky Figures consist of equal size blue and yellow circles.

Challenge 2 - Nine Circles: Set of Kandinsky Figures consist of 9 circles arranged in a regular grid.

Challenge 1 - Objects and Shapes: Ground truth gt(k) is defined as 'in a Kandinsky Figure small objects are arranged on big shapes same as object shapes, in the big shape of...

Kandinsky Patterns are mathematically describable, simple self-contained hence controllable test data sets for the development, validation and training of explainability in...

Explainability is a longstanding challenge in deep learning, especially in high-stakes domains like healthcare. Common explainability methods highlight image regions that drive...

Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. The dataset is used...

Explainable fake news detector with visualizations