# VALID: A perceptually validated Virtual Avatar Library for Inclusion and Diversity

arXiv: https://arxiv.org/abs/2309.10902 · HTML: https://mlsanity.com/paper/2309.10902/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2023.

## Built on by (most cited first, 2 of 2)

- [Mitigating Response Delays in Free-Form Conversations with LLM-powered Intelligent Virtual Agents](https://mlsanity.com/paper/2507.22352/) (2025)
- [Deepfake for the Good: Generating Avatars through Face-Swapping with Implicit Deepfake Generation](https://mlsanity.com/paper/2402.06390/) (2024)

## Abstract (arXiv)

As consumer adoption of immersive technologies grows, virtual avatars will play a prominent role in the future of social computing. However, as people begin to interact more frequently through virtual avatars, it is important to ensure that the research community has validated tools to evaluate the effects and consequences of such technologies. We present the first iteration of a new, freely available 3D avatar library called the Virtual Avatar Library for Inclusion and Diversity (VALID), which includes 210 fully rigged avatars with a focus on advancing racial diversity and inclusion. We present a detailed process for creating, iterating, and validating avatars of diversity. Through a large online study (n=132) with participants from 33 countries, we provide statistically validated labels for each avatar's perceived race and gender. Through our validation study, we also advance knowledge pertaining to the perception of an avatar's race. In particular, we found that avatars of some races were more accurately identified by participants of the same race.