all AI news
What matters when building vision-language models?
May 6, 2024, 4:45 a.m. | Hugo Lauren\c{c}on, L\'eo Tronchon, Matthieu Cord, Victor Sanh
cs.CV updates on arXiv.org arxiv.org
Abstract: The growing interest in vision-language models (VLMs) has been driven by improvements in large language models and vision transformers. Despite the abundance of literature on this subject, we observe that critical decisions regarding the design of VLMs are often not justified. We argue that these unsupported decisions impede progress in the field by making it difficult to identify which choices improve model performance. To address this issue, we conduct extensive experiments around pre-trained models, architecture …
abstract arxiv building cs.ai cs.cv decisions design improvements language language models large language large language models literature observe progress transformers type vision vision-language vision-language models vision transformers vlms
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US