Search Results for author:
Found 5 papers, 1 papers with code
Look Ma, No GANs! Image Transformation with ModifAE
Existing methods of image to image translation require multiple steps in the training or modification process, and suffer from either an inability to generalize, or long training times.
A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications
We present a framework for the automated measurement of responsible AI (RAI) metrics for large language models (LLMs) and associated products and services.
FairPrism: Evaluating Fairness-Related Harms in Text Generation
It is critical to measure and mitigate fairness- related harms caused by AI text generation systems, including stereotyping and demeaning harms.
When does text prediction benefit from additional context? An exploration of contextual signals for chat and email messages
We compare contextual text prediction in chat and email messages from two of the largest commercial platforms Microsoft Teams and Outlook, finding that contextual signals contribute to performance differently between these scenarios.
Learning to see people like people
Humans make complex inferences on faces, ranging from objective properties (gender, ethnicity, expression, age, identity, etc) to subjective judgments (facial attractiveness, trustworthiness, sociability, friendliness, etc).
