research
∙
05/22/2023
Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models
The generative AI revolution in recent years has been spurred by an expa...
share
research
∙
04/07/2022
Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality
We present a novel task and dataset for evaluating the ability of vision...
research
∙
04/05/2022
Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks
We introduce Dynatask: an open source system for setting up custom NLP t...
research
∙
12/16/2021
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants
In Dynamic Adversarial Data Collection (DADC), human annotators are task...
research
∙
09/09/2021
Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification
Research shows that natural language processing models are generally con...
research
∙
04/18/2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
When primed with only a handful of training samples, very large pretrain...
research
∙
04/18/2021
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation
Despite the availability of very large datasets and pretrained models, s...
research
∙
02/15/2020
Undersensitivity in Neural Reading Comprehension
Current reading comprehension models generalise well to in-distribution ...
research
∙
02/02/2020
Beat the AI: Investigating Adversarial Human Annotations for Reading Comprehension
Innovations in annotation methodology have been a propellant for Reading...
research
∙
08/28/2018
