5 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Hijacking Vision-and-Language Navigation Agents with Adversarial Environmental Attacks
Zijiao Yang, Xiangxi Shi, Eric Slyman +1
Assistive embodied agents that can be instructed in natural language to perform tasks in open-world environments have the potential to significantly impact labor tasks like manufac…
You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Models
Eric Slyman, Anirudh Kanneganti, Sanghyun Hong +1
We study the impact of a standard practice in compressing foundation vision-language models - quantization - on the models' ability to produce socially-fair outputs. In contrast to…
FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication
Eric Slyman, Stefan Lee, Scott Cohen +1
Recent dataset deduplication techniques have demonstrated that content-aware dataset pruning can dramatically reduce the cost of training Vision-Language Pretrained (VLP) models wi…
VLSlice: Interactive Vision-and-Language Slice Discovery
Eric Slyman, Minsuk Kahng, Stefan Lee
Recent work in vision-and-language demonstrates that large-scale pretraining can learn generalizable models that are efficiently transferable to downstream tasks. While this may im…