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Visual Question Answering Vqa On

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이 벤치마크에서 각 모델의 성능 결과

Paper Title
Gemini Ultra (pixel only)80.3Gemini: A Family of Highly Capable Multimodal Models
SMoLA-PaLI-X Specialist66.2Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts
ScreenAI 5B (4.62 B params, w/ OCR)65.90ScreenAI: A Vision-Language Model for UI and Infographics Understanding
SMoLA-PaLI-X Generalist65.6Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts
UDOP (aux)63.0Unifying Vision, Text, and Layout for Universal Document Processing
PaLI-3 (w/ OCR)62.4PaLI-3 Vision Language Models: Smaller, Faster, Stronger
TILT-Large61.20Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
PaLI-357.8PaLI-3 Vision Language Models: Smaller, Faster, Stronger
ChatGPT 3.5 with LAPDoc Prompt (SpatialFormat)54.9LAPDoc: Layout-Aware Prompting for Documents
PaLI-X (Single-task FT w/ OCR)54.8PaLI-X: On Scaling up a Multilingual Vision and Language Model
Claude + LATIN-Prompt54.51Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering
PaLI-X (Multi-task FT)50.7PaLI-X: On Scaling up a Multilingual Vision and Language Model
PaLI-X (Single-task FT)49.2PaLI-X: On Scaling up a Multilingual Vision and Language Model
GPT-3.5 + LATIN-Prompt48.98Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering
DocFormerv2-large48.8DocFormerv2: Local Features for Document Understanding
UDOP47.4Unifying Vision, Text, and Layout for Universal Document Processing
DUBLIN (variable resolution)42.6DUBLIN -- Document Understanding By Language-Image Network
Pix2Struct-large40Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
Pix2Struct-base38.2Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
MatCha37.2MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering
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Visual Question Answering Vqa On | SOTA | HyperAI초신경