paper-with-me

Visual Reasoning 벤치마크

Visual Reasoning on Winoground

114개 결과 · ⬇ CSV · JSON

Text Score

7 24.12 41.25 58.38 75.5 2022-04 2026-11 UNITER large — 38.0 (2022-04-07) VinVL — 37.75 (2022-04-07) ViLLA large — 37.0 (2022-04-07) ViLT (ViT-B/32) — 34.75 (2022-04-07) FLAVA (ITM) — 32.25 (2022-04-07) UNITER base — 32.25 (2022-04-07) CLIP (ViT-B/32) — 30.75 (2022-04-07) ViLLA base — 30.0 (2022-04-07) FLAVA (contrastive) — 25.25 (2022-04-07) Random chance — 25.0 (2022-04-07) ViLBERT base — 23.75 (2022-04-07) VSE++ (COCO, ResNet) — 22.75 (2022-04-07) VSRN (Flickr30k) — 20.0 (2022-04-07) VSE++ (Flickr30k, ResNet) — 20.0 (2022-04-07) VSE++ (Flickr30k, VGG) — 19.75 (2022-04-07) UniT (ITM finetuned) — 19.5 (2022-04-07) LXMERT — 19.25 (2022-04-07) VSE++ (COCO, VGG) — 18.75 (2022-04-07) VSRN (COCO) — 17.5 (2022-04-07) VisualBERT base — 15.5 (2022-04-07) IAIS large (Flickr30k) — 42.5 (2022-12-03) IAIS large (COCO) — 41.75 (2022-12-03) CACR base — 39.25 (2022-12-03) ROSITA (Flickr30k) — 35.25 (2022-12-03) ViT-B/16 + BERT base + ViLEM — 36.5 (2023-01-01) ViT-B/16 + BERT base — 31.2 (2023-01-01) FIBER (EqSim) — 51.5 (2023-03-25) FIBER (finetuned, Flickr30k) — 51.25 (2023-03-25) FIBER — 46.25 (2023-03-25) METER (EqSim) — 45.0 (2023-03-25) METER (finetuned, Flickr30k) — 43.5 (2023-03-25) METER — 39.25 (2023-03-25) Diffusion Classifier (zero-shot) — 34.0 (2023-03-28) syn-CLIP — 30.0 (2023-03-30) syn-CyCLIP — 30.0 (2023-03-30) CyCLIP — 28.5 (2023-03-30) BLIP2 (SGVL) — 42.8 (2023-05-10) BLIP (SGVL) — 42.8 (2023-05-10) NegBLIP — 42.5 (2023-05-10) BLIP2 — 42.0 (2023-05-10) NegBLIP2 — 41.5 (2023-05-10) BLIP (+Graph Text, +Graph Neg) — 40.5 (2023-05-10) BLIP (+Graph Text) — 40.3 (2023-05-10) BLIP — 39.0 (2023-05-10) CLIP (SGVL) — 32.0 (2023-05-10) NegCLIP — 29.5 (2023-05-10) LLaVA — 24.8 (2023-05-10) MiniGPT-4 — 23.3 (2023-05-10) OFA large (ITM) — 30.75 (2023-05-11) OFA large (TLC-A) — 29.25 (2023-05-11) OFA base (ITM) — 26.75 (2023-05-11) OFA base (TLC-A) — 24.5 (2023-05-11) OFA tiny (ITM) — 22.75 (2023-05-11) OFA tiny (TLC-A) — 16.5 (2023-05-11) X-VLM 16M — 46.7 (2023-05-12) X-VLM 4M — 44.0 (2023-05-12) BLIP 14M — 36.5 (2023-05-12) BLIP 129M — 35.5 (2023-05-12) BLIP 129M (CapFilt/L) — 34.7 (2023-05-12) BLIP-ViT/L 129M — 34.7 (2023-05-12) PEVL 14M — 33.2 (2023-05-12) ALBEF 14M — 32.5 (2023-05-12) ALBEF 4M — 29.2 (2023-05-12) VQ2 — 47.0 (2023-05-17) PaLI (ft SNLI-VE + Synthetic Data) — 46.5 (2023-05-17) PaLI (ft SNLI-VE) — 45.0 (2023-05-17) BLIP2 (ft COCO) — 44.0 (2023-05-17) COCA ViT-L14 (f.t on COCO) — 28.25 (2023-05-17) OFA large (ft SNLI-VE) — 27.7 (2023-05-17) CLIP RN50x64 — 26.5 (2023-05-17) TIFA — 19.0 (2023-05-17) BLIP (VisualGPTScore, α-tuned) — 36.5 (2023-06-02) BLIP (ITM) — 35.8 (2023-06-02) BLIP (ITC) — 28.0 (2023-06-02) LLaVA-7B (GPTScore) — 25.5 (2023-08-21) MiniGPT-4-7B (GPTScore) — 24.5 (2023-08-21) MiniGPT-4-7B (VisualGPTScore) — 23.25 (2023-08-21) MiniGPT-4-7B (BERTScore) — 14.0 (2023-08-21) LLaVA-7B (BERTScore) — 13.5 (2023-08-21) MMICL (FLAN-T5-XXL) — 45.5 (2023-09-14) GPT-4V (CoT, pick b/w two options) — 75.25 (2023-11-15) GPT-4V (pick b/w two options) — 69.25 (2023-11-15) OCLIP (ViT-H/14) — 30.75 (2023-11-17) CLIP (ViT-L/14) — 30.25 (2023-11-17) LDM-T5 (SelfEval) — 29.0 (2023-11-17) PDM-T5 (SelfEval) — 28.25 (2023-11-17) LDM-CLIP (SelfEval) — 22.75 (2023-11-17) PDM-CLIP (SelfEval) — 17.0 (2023-11-17) LLaVA-1.5-CCoT — 42.0 (2023-11-27) LLaVA-1.5 — 36.0 (2023-11-27) LLaVA-1.5-ZS-CoT — 28.0 (2023-11-27) InstructBLIP-CCoT — 21.0 (2023-11-27) InstructBLIP-ZS-CoT — 9.3 (2023-11-27) InstructBLIP — 7.0 (2023-11-27) MMICL + CoCoT — 64.25 (2024-01-05) GPT-4V + CoCoT — 58.5 (2024-01-05) OpenFlamingo + CoCoT — 58.25 (2024-01-05) GPT-4V — 54.5 (2024-01-05) MMICL + CCoT — 51.0 (2024-01-05) OpenFlamingo + DDCoT — 47.5 (2024-01-05) MMICL + DDCoT — 46.75 (2024-01-05) Gemini + DDCoT — 45.0 (2024-01-05) OpenFlamingo + CCoT — 42.5 (2024-01-05) Gemini + CoCoT — 40.0 (2024-01-05) OpenFlamingo — 39.0 (2024-01-05) Gemini — 30.75 (2024-01-05) Gemini + CCoT — 22.5 (2024-01-05) KeyComp* (GPT-4) — 43.5 (2024-01-20) KeyComp* (GPT-3.5) — 42.7 (2024-01-20) KeyComp (GPT-3.5) — 30.3 (2024-01-20) GPT-4o + CA — 75.5 (2025-01-23) UNITER large — 38.0 (2022-04-07) IAIS large (Flickr30k) — 42.5 (2022-12-03) FIBER (EqSim) — 51.5 (2023-03-25) GPT-4V (CoT, pick b/w two options) — 75.25 (2023-11-15) GPT-4o + CA — 75.5 (2025-01-23)
RankModel Text ScoreImage ScoreGroup Score PaperCodeYear
1 GPT-4o + CA 75.558.552 A Cognitive Paradigm Approach to Probe the Perception-Reasoning Interface in VLMs 2025
2 GPT-4V (CoT, pick b/w two options) 75.2568.7558.75 The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task 2023
3 GPT-4V (pick b/w two options) 69.2546.2539.25 The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task 2023
4 MMICL + CoCoT 64.2552.550.75 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
5 GPT-4V + CoCoT 58.549.544.5 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
6 OpenFlamingo + CoCoT 58.2555.2541.5 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
7 GPT-4V 54.542.537.75 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
8 FIBER (EqSim) 51.532.0027.5 Equivariant Similarity for Vision-Language Foundation Models wangt-cn/eqben 2023
9 FIBER (finetuned, Flickr30k) 51.2526.5023.00 Equivariant Similarity for Vision-Language Foundation Models wangt-cn/eqben 2023
10 MMICL + CCoT 514847.5 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
11 OpenFlamingo + DDCoT 47.547.2539 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
12 VQ2 4742.230.5 What You See is What You Read? Improving Text-Image Alignment Evaluation yonatanbitton/wysiwyr 2023
13 MMICL + DDCoT 46.754536.75 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
14 X-VLM 16M 46.724.521.2 Measuring Progress in Fine-grained Vision-and-Language Understanding e-bug/fine-grained-evals · e-bug/weak-relation-vlm 2023
15 PaLI (ft SNLI-VE + Synthetic Data) 46.53828.75 What You See is What You Read? Improving Text-Image Alignment Evaluation yonatanbitton/wysiwyr 2023
16 FIBER 46.2525.7522.25 Equivariant Similarity for Vision-Language Foundation Models wangt-cn/eqben 2023
17 MMICL (FLAN-T5-XXL) 45.5044.9943.00 MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning haozhezhao/mic · pkunlp-icler/mic 2023
18 PaLI (ft SNLI-VE) 45.0041.5028.70 What You See is What You Read? Improving Text-Image Alignment Evaluation yonatanbitton/wysiwyr 2023
18 Gemini + DDCoT 452523.75 CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs vista-h/gpt-4v_social_media 2024
18 METER (EqSim) 45.022.7518.75 Equivariant Similarity for Vision-Language Foundation Models wangt-cn/eqben 2023
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