EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

6 February 2024

Papers citing "EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters"

7 / 7 papers shown

Title
No Other Representation Component Is Needed: Diffusion Transformers Can Provide Representation Guidance by Themselves D. Jiang Mengmeng Wang Liuzhuozheng Li Lei Zhang Haoyu Wang Wei Wei Guang Dai Yanning Zhang Jingdong Wang DiffM 35 0 0 05 May 2025
Perception Encoder: The best visual embeddings are not at the output of the network Daniel Bolya Po-Yao (Bernie) Huang Peize Sun Jang Hyun Cho Andrea Madotto ... Shiyu Dong Nikhila Ravi Daniel Li Piotr Dollár Christoph Feichtenhofer ObjD VOS 98 0 0 17 Apr 2025
OmniBal: Towards Fast Instruct-tuning for Vision-Language Models via Omniverse Computation Balance Yongqiang Yao Jingru Tan Jiahao Hu Feizhao Zhang Xin Jin ... Ruihao Gong Pengfei Liu Pengfei Liu Dahua Lin Ningyi Xu VLM 30 1 0 30 Jul 2024
On Efficient Language and Vision Assistants for Visually-Situated Natural Language Understanding: What Matters in Reading and Reasoning Geewook Kim Minjoon Seo VLM 14 2 0 17 Jun 2024
Scaling White-Box Transformers for Vision Jinrui Yang Xianhang Li Druv Pai Yuyin Zhou Yi-An Ma Yaodong Yu Cihang Xie ViT 30 9 0 30 May 2024
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks Zhe Chen Jiannan Wu Wenhai Wang Weijie Su Guo Chen ... Bin Li Ping Luo Tong Lu Yu Qiao Jifeng Dai VLM MLLM 126 895 0 21 Dec 2023
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models Junnan Li Dongxu Li Silvio Savarese Steven C. H. Hoi VLM MLLM 244 4,186 0 30 Jan 2023