3 papers
cs.CV2024
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling
Haider Al-Tahan, Quentin Garrido, Randall Balestriero +3
Significant research efforts have been made to scale and improve vision-language model (VLM) training approaches. Yet, with an ever-growing number of benchmarks, researchers are ta…
cs.CV2024
The Bias of Harmful Label Associations in Vision-Language Models
Caner Hazirbas, Alicia Sun, Yonathan Efroni +1
Despite the remarkable performance of foundation vision-language models, the shared representation space for text and vision can also encode harmful label associations detrimental…
cs.CV2023
VPA: Fully Test-Time Visual Prompt Adaptation
Jiachen Sun, Mark Ibrahim, Melissa Hall +4
Textual prompt tuning has demonstrated significant performance improvements in adapting natural language processing models to a variety of downstream tasks by treating hand-enginee…