5 citations · 5 across the 5 of their papers we have counts for
6 papers
Direct Translation between Sign Languages
Zetian Wu, Bowen Xie, Wuyang Meng +3
Sign language translation has made substantial progress between sign and spoken languages, while translation across sign languages remains less explored. Translating directly betwe…
Calibrating MLLM-as-a-judge via Multimodal Bayesian Prompt Ensembles
Eric Slyman, Mehrab Tanjim, Kushal Kafle +1
Multimodal large language models (MLLMs) are increasingly used to evaluate text-to-image (TTI) generation systems, providing automated judgments based on visual and textual context…
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…