The SCIN dataset contains 10,000+ images of dermatology conditions, crowdsourced with informed consent from US internet users. Contributions include self-reported demographic and symptom information and dermatologist labels. The dataset also contains estimated Fitzpatrick skin type and Monk Skin Tone.

MISeD (Meeting Information Seeking Dialogs dataset) is an information-seeking dialog dataset focused on meeting transcripts. It includes 432 dialogs over transcripts from the QMSum dataset. MISeD is described in detail in the paper: Efficient Data Generation for Source-grounded Information-seeking Dialogs: A Use Case for Meeting Transcripts.

UICrit is a dataset containing human-generated natural language design critiques, corresponding bounding boxes for each critique, and design quality ratings for 1,000 mobile UIs from RICO. This dataset was collected for our UIST '24 paper: https://arxiv.org/abs/2407.08850.

The HierText dataset contains ~12k images from the Open Images dataset v6 with large amount of text entities. We provide word, line and paragraph level annotations.

The WordGraph dataset contains multilingual lexicon entries linked to wikipedia entities, focusing on human-denoting names and demonym adjectives. Each lexicon entries contain inflected word-form and morphological information all locales.

Dataset of conversations, generated by prompting Gemini Ultra. These are conversations between a teacher and a student, where the teacher is prompted with specific topic to teach the student, and the student is prompted with their learning preferences. https://arxiv.org/abs/2405.14655

GeniL dataset is an effort for detecting various types of generalization in language. This multilingual dataset covers sentences in EN, FR, ES, PT, AR, HI, BN, MS, and ID and is annotated by native speakers of each language. Each sentence is collected from a public corpora of language and contains at least one identity group name and an attribute.

The Tap Typing with Touch Sensing Images (TSI) dataset contains data of user taps on a mobile touchscreen keyboard, including elliptical features and capacitive sensing images of the taps. The dataset aligns each tap with a key the user intended to type during data collection so it can be used for keyboard decoder training and/or evaluation.

Datasets for measuring misgendering in translation