paper-with-me

Visual Question Answering (VQA) 벤치마크

Visual Question Answering (VQA) on AI2D

4개 결과 · ⬇ CSV · JSON

EM

51.11 58.96 66.81 74.65 82.5 2023-05 2026-09 DUBLIN — 51.11 (2023-05-23) SMoLA-PaLI-X Specialist Model — 82.5 (2023-12-01) SMoLA-PaLI-X Generalist Model — 81.4 (2023-12-01) Gemini Ultra — 79.5 (2023-12-19) DUBLIN — 51.11 (2023-05-23) SMoLA-PaLI-X Specialist Model — 82.5 (2023-12-01)
RankModel EM Extra Training Data PaperCodeYear
1 SMoLA-PaLI-X Specialist Model 82.5 Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts 2023
2 SMoLA-PaLI-X Generalist Model 81.4 Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts 2023
3 Gemini Ultra 79.5 Gemini: A Family of Highly Capable Multimodal Models valdecy/pybibx 2023
4 DUBLIN 51.11 DUBLIN -- Document Understanding By Language-Image Network 2023
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