5 citations · 6 across the 6 of their papers we have counts for
6 papers
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…
On the Behavior of Audio-Visual Fusion Architectures in Identity Verification Tasks
Daniel Claborne, Eric Slyman, Karl Pazdernik
We train an identity verification architecture and evaluate modifications to the part of the model that combines audio and visual representations, including in scenarios where one…
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…
Fine-Grained Classroom Activity Detection from Audio with Neural Networks
Eric Slyman, Chris Daw, Morgan Skrabut +2
Instructors are increasingly incorporating student-centered learning techniques in their classrooms to improve learning outcomes. In addition to lecture, these class sessions invol…