Upload folder using huggingface_hub
Browse files- A-OKVQA/test-00000-of-00001.parquet +3 -0
- CIFAR-100/test-00000-of-00001.parquet +3 -0
- CIRR/test-00000-of-00001.parquet +3 -0
- ChartQA/test-00000-of-00001.parquet +3 -0
- Country211/test-00000-of-00001.parquet +3 -0
- DocVQA/test-00000-of-00001.parquet +3 -0
- EDIS/test-00000-of-00001.parquet +3 -0
- FashionIQ/test-00000-of-00001.parquet +3 -0
- GQA/test-00000-of-00001.parquet +3 -0
- HatefulMemes/test-00000-of-00001.parquet +3 -0
- ImageNet-1K/test-00000-of-00001.parquet +3 -0
- ImageNet-A/test-00000-of-00001.parquet +3 -0
- ImageNet-R/test-00000-of-00001.parquet +3 -0
- InfographicsVQA/test-00000-of-00001.parquet +3 -0
- MSCOCO/test-00000-of-00001.parquet +3 -0
- MSCOCO_i2t/test-00000-of-00001.parquet +3 -0
- MSCOCO_t2i/test-00000-of-00001.parquet +3 -0
- N24News/test-00000-of-00001.parquet +3 -0
- NIGHTS/test-00000-of-00001.parquet +3 -0
- OK-VQA/test-00000-of-00001.parquet +3 -0
- OVEN/test-00000-of-00001.parquet +3 -0
- ObjectNet/test-00000-of-00001.parquet +3 -0
- Place365/test-00000-of-00001.parquet +3 -0
- README.md +930 -3
- RefCOCO-Matching/test-00000-of-00001.parquet +3 -0
- RefCOCO/test-00000-of-00001.parquet +3 -0
- SUN397/test-00000-of-00001.parquet +3 -0
- ScienceQA/test-00000-of-00001.parquet +3 -0
- TextVQA/test-00000-of-00001.parquet +3 -0
- VOC2007/test-00000-of-00001.parquet +3 -0
- VisDial/test-00000-of-00001.parquet +3 -0
- Visual7W-Pointing/test-00000-of-00001.parquet +3 -0
- Visual7W/test-00000-of-00001.parquet +3 -0
- VisualNews_i2t/test-00000-of-00001.parquet +3 -0
- VisualNews_t2i/test-00000-of-00001.parquet +3 -0
- VizWiz/test-00000-of-00001.parquet +3 -0
- WebQA/test-00000-of-00001.parquet +3 -0
- Wiki-SS-NQ/test-00000-of-00001.parquet +3 -0
A-OKVQA/test-00000-of-00001.parquet
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CIFAR-100/test-00000-of-00001.parquet
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CIRR/test-00000-of-00001.parquet
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ChartQA/test-00000-of-00001.parquet
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Country211/test-00000-of-00001.parquet
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DocVQA/test-00000-of-00001.parquet
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EDIS/test-00000-of-00001.parquet
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FashionIQ/test-00000-of-00001.parquet
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GQA/test-00000-of-00001.parquet
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HatefulMemes/test-00000-of-00001.parquet
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ImageNet-1K/test-00000-of-00001.parquet
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ImageNet-A/test-00000-of-00001.parquet
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ImageNet-R/test-00000-of-00001.parquet
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InfographicsVQA/test-00000-of-00001.parquet
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MSCOCO/test-00000-of-00001.parquet
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MSCOCO_i2t/test-00000-of-00001.parquet
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MSCOCO_t2i/test-00000-of-00001.parquet
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N24News/test-00000-of-00001.parquet
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NIGHTS/test-00000-of-00001.parquet
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OK-VQA/test-00000-of-00001.parquet
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OVEN/test-00000-of-00001.parquet
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ObjectNet/test-00000-of-00001.parquet
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Place365/test-00000-of-00001.parquet
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README.md
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-
---
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1 |
+
---
|
2 |
+
dataset_info:
|
3 |
+
- config_name: A-OKVQA
|
4 |
+
features:
|
5 |
+
- name: qry_text
|
6 |
+
dtype: string
|
7 |
+
- name: qry_img_path
|
8 |
+
dtype: string
|
9 |
+
- name: tgt_text
|
10 |
+
sequence: string
|
11 |
+
- name: tgt_img_path
|
12 |
+
sequence: string
|
13 |
+
- name: task_instruction
|
14 |
+
dtype: string
|
15 |
+
- name: represent_prompt
|
16 |
+
dtype: string
|
17 |
+
splits:
|
18 |
+
- name: test
|
19 |
+
num_bytes: 14048199
|
20 |
+
num_examples: 1000
|
21 |
+
download_size: 1168340
|
22 |
+
dataset_size: 14048199
|
23 |
+
- config_name: CIFAR-100
|
24 |
+
features:
|
25 |
+
- name: qry_text
|
26 |
+
dtype: string
|
27 |
+
- name: qry_img_path
|
28 |
+
dtype: string
|
29 |
+
- name: tgt_text
|
30 |
+
sequence: string
|
31 |
+
- name: tgt_img_path
|
32 |
+
sequence: string
|
33 |
+
- name: task_instruction
|
34 |
+
dtype: string
|
35 |
+
- name: represent_prompt
|
36 |
+
dtype: string
|
37 |
+
splits:
|
38 |
+
- name: test
|
39 |
+
num_bytes: 1519890
|
40 |
+
num_examples: 1000
|
41 |
+
download_size: 20544
|
42 |
+
dataset_size: 1519890
|
43 |
+
- config_name: CIRR
|
44 |
+
features:
|
45 |
+
- name: qry_text
|
46 |
+
dtype: string
|
47 |
+
- name: qry_img_path
|
48 |
+
dtype: string
|
49 |
+
- name: tgt_text
|
50 |
+
sequence: string
|
51 |
+
- name: tgt_img_path
|
52 |
+
sequence: string
|
53 |
+
- name: task_instruction
|
54 |
+
dtype: string
|
55 |
+
- name: represent_prompt
|
56 |
+
dtype: string
|
57 |
+
splits:
|
58 |
+
- name: test
|
59 |
+
num_bytes: 70162098
|
60 |
+
num_examples: 1000
|
61 |
+
download_size: 1565489
|
62 |
+
dataset_size: 70162098
|
63 |
+
- config_name: ChartQA
|
64 |
+
features:
|
65 |
+
- name: qry_text
|
66 |
+
dtype: string
|
67 |
+
- name: qry_img_path
|
68 |
+
dtype: string
|
69 |
+
- name: tgt_text
|
70 |
+
sequence: string
|
71 |
+
- name: tgt_img_path
|
72 |
+
sequence: string
|
73 |
+
- name: task_instruction
|
74 |
+
dtype: string
|
75 |
+
- name: represent_prompt
|
76 |
+
dtype: string
|
77 |
+
splits:
|
78 |
+
- name: test
|
79 |
+
num_bytes: 14354641
|
80 |
+
num_examples: 1000
|
81 |
+
download_size: 1434448
|
82 |
+
dataset_size: 14354641
|
83 |
+
- config_name: Country211
|
84 |
+
features:
|
85 |
+
- name: qry_text
|
86 |
+
dtype: string
|
87 |
+
- name: qry_img_path
|
88 |
+
dtype: string
|
89 |
+
- name: tgt_text
|
90 |
+
sequence: string
|
91 |
+
- name: tgt_img_path
|
92 |
+
sequence: string
|
93 |
+
- name: task_instruction
|
94 |
+
dtype: string
|
95 |
+
- name: represent_prompt
|
96 |
+
dtype: string
|
97 |
+
splits:
|
98 |
+
- name: test
|
99 |
+
num_bytes: 3678000
|
100 |
+
num_examples: 1000
|
101 |
+
download_size: 31556
|
102 |
+
dataset_size: 3678000
|
103 |
+
- config_name: DocVQA
|
104 |
+
features:
|
105 |
+
- name: qry_text
|
106 |
+
dtype: string
|
107 |
+
- name: qry_img_path
|
108 |
+
dtype: string
|
109 |
+
- name: tgt_text
|
110 |
+
sequence: string
|
111 |
+
- name: tgt_img_path
|
112 |
+
sequence: string
|
113 |
+
- name: task_instruction
|
114 |
+
dtype: string
|
115 |
+
- name: represent_prompt
|
116 |
+
dtype: string
|
117 |
+
splits:
|
118 |
+
- name: test
|
119 |
+
num_bytes: 23044459
|
120 |
+
num_examples: 1000
|
121 |
+
download_size: 1734476
|
122 |
+
dataset_size: 23044459
|
123 |
+
- config_name: EDIS
|
124 |
+
features:
|
125 |
+
- name: qry_text
|
126 |
+
dtype: string
|
127 |
+
- name: qry_img_path
|
128 |
+
dtype: string
|
129 |
+
- name: tgt_text
|
130 |
+
sequence: string
|
131 |
+
- name: tgt_img_path
|
132 |
+
sequence: string
|
133 |
+
- name: task_instruction
|
134 |
+
dtype: string
|
135 |
+
- name: represent_prompt
|
136 |
+
dtype: string
|
137 |
+
splits:
|
138 |
+
- name: test
|
139 |
+
num_bytes: 184208708
|
140 |
+
num_examples: 1000
|
141 |
+
download_size: 3350382
|
142 |
+
dataset_size: 184208708
|
143 |
+
- config_name: FashionIQ
|
144 |
+
features:
|
145 |
+
- name: qry_text
|
146 |
+
dtype: string
|
147 |
+
- name: qry_img_path
|
148 |
+
dtype: string
|
149 |
+
- name: tgt_text
|
150 |
+
sequence: string
|
151 |
+
- name: tgt_img_path
|
152 |
+
sequence: string
|
153 |
+
- name: task_instruction
|
154 |
+
dtype: string
|
155 |
+
- name: represent_prompt
|
156 |
+
dtype: string
|
157 |
+
splits:
|
158 |
+
- name: test
|
159 |
+
num_bytes: 71169665
|
160 |
+
num_examples: 1000
|
161 |
+
download_size: 1729457
|
162 |
+
dataset_size: 71169665
|
163 |
+
- config_name: GQA
|
164 |
+
features:
|
165 |
+
- name: qry_text
|
166 |
+
dtype: string
|
167 |
+
- name: qry_img_path
|
168 |
+
dtype: string
|
169 |
+
- name: tgt_text
|
170 |
+
sequence: string
|
171 |
+
- name: tgt_img_path
|
172 |
+
sequence: string
|
173 |
+
- name: task_instruction
|
174 |
+
dtype: string
|
175 |
+
- name: represent_prompt
|
176 |
+
dtype: string
|
177 |
+
splits:
|
178 |
+
- name: test
|
179 |
+
num_bytes: 40809641
|
180 |
+
num_examples: 1000
|
181 |
+
download_size: 1764457
|
182 |
+
dataset_size: 40809641
|
183 |
+
- config_name: HatefulMemes
|
184 |
+
features:
|
185 |
+
- name: qry_text
|
186 |
+
dtype: string
|
187 |
+
- name: qry_img_path
|
188 |
+
dtype: string
|
189 |
+
- name: tgt_text
|
190 |
+
sequence: string
|
191 |
+
- name: tgt_img_path
|
192 |
+
sequence: string
|
193 |
+
- name: task_instruction
|
194 |
+
dtype: string
|
195 |
+
- name: represent_prompt
|
196 |
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dtype: string
|
197 |
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splits:
|
198 |
+
- name: test
|
199 |
+
num_bytes: 184890
|
200 |
+
num_examples: 1000
|
201 |
+
download_size: 9972
|
202 |
+
dataset_size: 184890
|
203 |
+
- config_name: ImageNet-1K
|
204 |
+
features:
|
205 |
+
- name: qry_text
|
206 |
+
dtype: string
|
207 |
+
- name: qry_img_path
|
208 |
+
dtype: string
|
209 |
+
- name: tgt_text
|
210 |
+
sequence: string
|
211 |
+
- name: tgt_img_path
|
212 |
+
sequence: string
|
213 |
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- name: task_instruction
|
214 |
+
dtype: string
|
215 |
+
- name: represent_prompt
|
216 |
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dtype: string
|
217 |
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splits:
|
218 |
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- name: test
|
219 |
+
num_bytes: 28773890
|
220 |
+
num_examples: 1000
|
221 |
+
download_size: 185019
|
222 |
+
dataset_size: 28773890
|
223 |
+
- config_name: ImageNet-A
|
224 |
+
features:
|
225 |
+
- name: qry_text
|
226 |
+
dtype: string
|
227 |
+
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|
228 |
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dtype: string
|
229 |
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- name: tgt_text
|
230 |
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sequence: string
|
231 |
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- name: tgt_img_path
|
232 |
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sequence: string
|
233 |
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|
234 |
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dtype: string
|
235 |
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|
236 |
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dtype: string
|
237 |
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splits:
|
238 |
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- name: test
|
239 |
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num_bytes: 28772890
|
240 |
+
num_examples: 1000
|
241 |
+
download_size: 147780
|
242 |
+
dataset_size: 28772890
|
243 |
+
- config_name: ImageNet-R
|
244 |
+
features:
|
245 |
+
- name: qry_text
|
246 |
+
dtype: string
|
247 |
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dtype: string
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sequence: string
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sequence: string
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dtype: string
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splits:
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num_bytes: 3456890
|
260 |
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num_examples: 1000
|
261 |
+
download_size: 23656
|
262 |
+
dataset_size: 3456890
|
263 |
+
- config_name: InfographicsVQA
|
264 |
+
features:
|
265 |
+
- name: qry_text
|
266 |
+
dtype: string
|
267 |
+
- name: qry_img_path
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num_bytes: 19114439
|
280 |
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num_examples: 1000
|
281 |
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download_size: 1439837
|
282 |
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dataset_size: 19114439
|
283 |
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- config_name: MSCOCO
|
284 |
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features:
|
285 |
+
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|
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dtype: string
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|
300 |
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|
301 |
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download_size: 1681753
|
302 |
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dataset_size: 97759085
|
303 |
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- config_name: MSCOCO_i2t
|
304 |
+
features:
|
305 |
+
- name: qry_text
|
306 |
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320 |
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num_examples: 1000
|
321 |
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download_size: 1785583
|
322 |
+
dataset_size: 60201740
|
323 |
+
- config_name: MSCOCO_t2i
|
324 |
+
features:
|
325 |
+
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326 |
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dtype: string
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|
340 |
+
num_examples: 1000
|
341 |
+
download_size: 1296167
|
342 |
+
dataset_size: 87127008
|
343 |
+
- config_name: N24News
|
344 |
+
features:
|
345 |
+
- name: qry_text
|
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+
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|
347 |
+
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820 |
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- config_name: OK-VQA
|
821 |
+
data_files:
|
822 |
+
- split: test
|
823 |
+
path: OK-VQA/test-*
|
824 |
+
- config_name: OVEN
|
825 |
+
data_files:
|
826 |
+
- split: test
|
827 |
+
path: OVEN/test-*
|
828 |
+
- config_name: ObjectNet
|
829 |
+
data_files:
|
830 |
+
- split: test
|
831 |
+
path: ObjectNet/test-*
|
832 |
+
- config_name: Place365
|
833 |
+
data_files:
|
834 |
+
- split: test
|
835 |
+
path: Place365/test-*
|
836 |
+
- config_name: RefCOCO
|
837 |
+
data_files:
|
838 |
+
- split: test
|
839 |
+
path: RefCOCO/test-*
|
840 |
+
- config_name: RefCOCO-Matching
|
841 |
+
data_files:
|
842 |
+
- split: test
|
843 |
+
path: RefCOCO-Matching/test-*
|
844 |
+
- config_name: SUN397
|
845 |
+
data_files:
|
846 |
+
- split: test
|
847 |
+
path: SUN397/test-*
|
848 |
+
- config_name: ScienceQA
|
849 |
+
data_files:
|
850 |
+
- split: test
|
851 |
+
path: ScienceQA/test-*
|
852 |
+
- config_name: TextVQA
|
853 |
+
data_files:
|
854 |
+
- split: test
|
855 |
+
path: TextVQA/test-*
|
856 |
+
- config_name: VOC2007
|
857 |
+
data_files:
|
858 |
+
- split: test
|
859 |
+
path: VOC2007/test-*
|
860 |
+
- config_name: VisDial
|
861 |
+
data_files:
|
862 |
+
- split: test
|
863 |
+
path: VisDial/test-*
|
864 |
+
- config_name: Visual7W
|
865 |
+
data_files:
|
866 |
+
- split: test
|
867 |
+
path: Visual7W/test-*
|
868 |
+
- config_name: Visual7W-Pointing
|
869 |
+
data_files:
|
870 |
+
- split: test
|
871 |
+
path: Visual7W-Pointing/test-*
|
872 |
+
- config_name: VisualNews_i2t
|
873 |
+
data_files:
|
874 |
+
- split: test
|
875 |
+
path: VisualNews_i2t/test-*
|
876 |
+
- config_name: VisualNews_t2i
|
877 |
+
data_files:
|
878 |
+
- split: test
|
879 |
+
path: VisualNews_t2i/test-*
|
880 |
+
- config_name: VizWiz
|
881 |
+
data_files:
|
882 |
+
- split: test
|
883 |
+
path: VizWiz/test-*
|
884 |
+
- config_name: WebQA
|
885 |
+
data_files:
|
886 |
+
- split: test
|
887 |
+
path: WebQA/test-*
|
888 |
+
- config_name: Wiki-SS-NQ
|
889 |
+
data_files:
|
890 |
+
- split: test
|
891 |
+
path: Wiki-SS-NQ/test-*
|
892 |
+
license: apache-2.0
|
893 |
+
language:
|
894 |
+
- en
|
895 |
+
tags:
|
896 |
+
- ranking
|
897 |
+
pretty_name: MMEB
|
898 |
+
size_categories:
|
899 |
+
- 10K<n<100K
|
900 |
+
---
|
901 |
+
|
902 |
+
# Massive Multimodal Embedding Benchmark
|
903 |
+
|
904 |
+
We compile a large set of evaluation tasks to understand the capabilities of multimodal embedding models. This benchmark covers 4 meta tasks and 36 datasets meticulously selected for evaluation.
|
905 |
+
|
906 |
+
The dataset is published in our paper [VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks](https://arxiv.org/abs/2410.05160).
|
907 |
+
|
908 |
+
## Dataset Usage
|
909 |
+
For each dataset, we have 1000 examples for evaluation. Each example contains a query and a set of targets. Both the query and target could be any combination of image and text. The first one in the candidate list is the groundtruth target.
|
910 |
+
|
911 |
+
## Statistics
|
912 |
+
We show the statistics of all the datasets as follows:
|
913 |
+
<img width="900" alt="abs" src="statistics.png">
|
914 |
+
|
915 |
+
## Per-dataset Results
|
916 |
+
We list the performance of different embedding models in the following:
|
917 |
+
<img width="900" alt="abs" src="leaderboard.png">
|
918 |
+
|
919 |
+
## Submission
|
920 |
+
We will set a formal leaderboard soon. If you want to add your results to the leaderboard, please send email to us at [email protected].
|
921 |
+
|
922 |
+
## Cite Us
|
923 |
+
```
|
924 |
+
@article{jiang2024vlm2vec,
|
925 |
+
title={VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks},
|
926 |
+
author={Jiang, Ziyan and Meng, Rui and Yang, Xinyi and Yavuz, Semih and Zhou, Yingbo and Chen, Wenhu},
|
927 |
+
journal={arXiv preprint arXiv:2410.05160},
|
928 |
+
year={2024}
|
929 |
+
}
|
930 |
+
```
|
RefCOCO-Matching/test-00000-of-00001.parquet
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VOC2007/test-00000-of-00001.parquet
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VisDial/test-00000-of-00001.parquet
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Visual7W-Pointing/test-00000-of-00001.parquet
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VisualNews_i2t/test-00000-of-00001.parquet
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