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Visual Reasoning
Visual Reasoning On Winoground
Visual Reasoning On Winoground
Metrics
Group Score
Image Score
Text Score
Results
Performance results of various models on this benchmark
Columns
Model Name
Group Score
Image Score
Text Score
Paper Title
Repository
ViLBERT base
4.75
7.25
23.75
Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality
METER (finetuned, Flickr30k)
14.75
20.75
43.5
Equivariant Similarity for Vision-Language Foundation Models
BLIP (ITM)
13.3
15.8
35.8
Revisiting the Role of Language Priors in Vision-Language Models
BLIP2 (SGVL)
23.3
28.5
42.8
Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs
-
Gemini + CoCoT
27.75
32.5
40
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
GPT-4V (CoT, pick b/w two options)
58.75
68.75
75.25
The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task
-
OpenFlamingo + CoCoT
41.5
55.25
58.25
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
COCA ViT-L14 (f.t on COCO)
8.25
11.50
28.25
What You See is What You Read? Improving Text-Image Alignment Evaluation
OFA large (ITM)
7.25
10.25
30.75
Simple Token-Level Confidence Improves Caption Correctness
-
VSE++ (COCO, VGG)
3.50
5.50
18.75
Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality
METER
12.00
15.75
39.25
Equivariant Similarity for Vision-Language Foundation Models
OpenFlamingo
33.25
41.25
39
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
LDM-CLIP (SelfEval)
-
7.25
22.75
SelfEval: Leveraging the discriminative nature of generative models for evaluation
-
CLIP (ViT-L/14)
-
8.0
30.25
SelfEval: Leveraging the discriminative nature of generative models for evaluation
-
BLIP 129M (CapFilt/L)
12.2
15.2
34.7
Measuring Progress in Fine-grained Vision-and-Language Understanding
KeyComp* (GPT-4)
18.2
28.7
43.5
Prompting Large Vision-Language Models for Compositional Reasoning
LLaVA-7B (GPTScore)
10.50
17.00
25.50
An Examination of the Compositionality of Large Generative Vision-Language Models
TIFA
11.30
12.50
19.00
What You See is What You Read? Improving Text-Image Alignment Evaluation
Diffusion Classifier (zero-shot)
-
-
34.00
Your Diffusion Model is Secretly a Zero-Shot Classifier
KeyComp* (GPT-3.5)
17.4
27.8
42.7
Prompting Large Vision-Language Models for Compositional Reasoning
0 of 113 row(s) selected.
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