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README.md
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---
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dataset_info:
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- config_name: default
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features:
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- name: LPimage
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dtype: image
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- name: image1
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dtype: image
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- name: image2
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dtype: image
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- name: image3
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dtype: image
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- name: image4
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dtype: image
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- name: image5
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dtype: image
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- name: annotator1_ranking
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sequence: int32
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length: 5
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- name: annotator1_best
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dtype: int32
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- name: annotator1_worst
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dtype: int32
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- name: annotator2_ranking
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sequence: int32
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length: 5
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- name: annotator2_best
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dtype: int32
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- name: annotator2_worst
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dtype: int32
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- name: annotator3_ranking
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sequence: int32
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length: 5
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- name: annotator3_best
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dtype: int32
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- name: annotator3_worst
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dtype: int32
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- name: annotator4_ranking
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sequence: int32
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length: 5
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- name: annotator4_best
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dtype: int32
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- name: annotator4_worst
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dtype: int32
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- name: annotator5_ranking
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sequence: int32
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length: 5
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- name: annotator5_best
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dtype: int32
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- name: annotator5_worst
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dtype: int32
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- name: best_annotator
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dtype: string
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- name: average_rank_correlation
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dtype: float32
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license: cc-by-nc-sa-4.0
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task_categories:
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- visual-question-answering
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language:
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- ja
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size_categories:
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- n<1K
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---
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# BannerBench: Benchmarking Vision Language Models for Multi-Ad Selection with Human Preferences
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@@ -155,10 +155,9 @@ AdTEC dataset is released under the [CreativeCommons Attribution-NonCommercial-S
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### Citation Information
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To cite this work, please use the following format:
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```
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{
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author = {Hiroto Otake and Peinan Zhang and Yusuke Sakai and Masato Mita and Hiroki Ouchi and Taro Watanabe},
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title = {BannerBench: Benchmarking Vision Language Models for Multi-Ad Selection with Human Preferences},
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year = {2025}
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url = {}
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}
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```
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+
---
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| 2 |
+
dataset_info:
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| 3 |
+
- config_name: default
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| 4 |
+
features:
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| 5 |
+
- name: LPimage
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| 6 |
+
dtype: image
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| 7 |
+
- name: image1
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| 8 |
+
dtype: image
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| 9 |
+
- name: image2
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| 10 |
+
dtype: image
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| 11 |
+
- name: image3
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| 12 |
+
dtype: image
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| 13 |
+
- name: image4
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| 14 |
+
dtype: image
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+
- name: image5
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+
dtype: image
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+
- name: annotator1_ranking
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+
sequence: int32
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+
length: 5
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+
- name: annotator1_best
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+
dtype: int32
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+
- name: annotator1_worst
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+
dtype: int32
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+
- name: annotator2_ranking
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+
sequence: int32
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+
length: 5
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+
- name: annotator2_best
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+
dtype: int32
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+
- name: annotator2_worst
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+
dtype: int32
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+
- name: annotator3_ranking
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+
sequence: int32
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+
length: 5
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+
- name: annotator3_best
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+
dtype: int32
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+
- name: annotator3_worst
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+
dtype: int32
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+
- name: annotator4_ranking
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+
sequence: int32
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+
length: 5
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| 41 |
+
- name: annotator4_best
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+
dtype: int32
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| 43 |
+
- name: annotator4_worst
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| 44 |
+
dtype: int32
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| 45 |
+
- name: annotator5_ranking
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| 46 |
+
sequence: int32
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| 47 |
+
length: 5
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| 48 |
+
- name: annotator5_best
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+
dtype: int32
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+
- name: annotator5_worst
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| 51 |
+
dtype: int32
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+
- name: best_annotator
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+
dtype: string
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| 54 |
+
- name: average_rank_correlation
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+
dtype: float32
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license: cc-by-nc-sa-4.0
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+
task_categories:
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- visual-question-answering
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+
language:
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- ja
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size_categories:
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+
- n<1K
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---
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# BannerBench: Benchmarking Vision Language Models for Multi-Ad Selection with Human Preferences
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|
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### Citation Information
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To cite this work, please use the following format:
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```
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@misc{otake2025banner,
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author = {Hiroto Otake and Peinan Zhang and Yusuke Sakai and Masato Mita and Hiroki Ouchi and Taro Watanabe},
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title = {BannerBench: Benchmarking Vision Language Models for Multi-Ad Selection with Human Preferences},
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year = {2025}
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}
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```
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