Datasets:

lmms-lab
/

POPE

id stringlengths 1 4	question_id stringlengths 1 4	question stringclasses 86 values	answer stringclasses 2 values	image_source stringclasses 500 values	category stringclasses 3 values
0	1	Is there a snowboard in the image?	yes	COCO_val2014_000000310196	adversarial
1	2	Is there a backpack in the image?	no	COCO_val2014_000000310196	adversarial
2	3	Is there a person in the image?	yes	COCO_val2014_000000310196	adversarial
3	4	Is there a car in the image?	no	COCO_val2014_000000310196	adversarial
4	5	Is there a skis in the image?	yes	COCO_val2014_000000310196	adversarial
5	6	Is there a dog in the image?	no	COCO_val2014_000000310196	adversarial
6	7	Is there a truck in the image?	yes	COCO_val2014_000000210789	adversarial
7	8	Is there a car in the image?	no	COCO_val2014_000000210789	adversarial
8	9	Is there a person in the image?	yes	COCO_val2014_000000210789	adversarial
9	10	Is there a dining table in the image?	no	COCO_val2014_000000210789	adversarial
10	11	Is there an umbrella in the imange?	yes	COCO_val2014_000000210789	adversarial
11	12	Is there a handbag in the image?	no	COCO_val2014_000000210789	adversarial
12	13	Is there a person in the image?	yes	COCO_val2014_000000429109	adversarial
13	14	Is there a dining table in the image?	no	COCO_val2014_000000429109	adversarial
14	15	Is there a bicycle in the image?	yes	COCO_val2014_000000429109	adversarial
15	16	Is there a motorcycle in the image?	no	COCO_val2014_000000429109	adversarial
16	17	Is there a car in the image?	yes	COCO_val2014_000000429109	adversarial
17	18	Is there a truck in the image?	no	COCO_val2014_000000429109	adversarial
18	19	Is there a person in the image?	yes	COCO_val2014_000000211674	adversarial
19	20	Is there a dining table in the image?	no	COCO_val2014_000000211674	adversarial
20	21	Is there a potted plant in the image?	yes	COCO_val2014_000000211674	adversarial
21	22	Is there a vase in the image?	no	COCO_val2014_000000211674	adversarial
22	23	Is there a car in the image?	yes	COCO_val2014_000000211674	adversarial
23	24	Is there a truck in the image?	no	COCO_val2014_000000211674	adversarial
24	25	Is there a traffic light in the image?	yes	COCO_val2014_000000458338	adversarial
25	26	Is there a bus in the image?	no	COCO_val2014_000000458338	adversarial
26	27	Is there a person in the image?	yes	COCO_val2014_000000458338	adversarial
27	28	Is there a dining table in the image?	no	COCO_val2014_000000458338	adversarial
28	29	Is there a car in the image?	yes	COCO_val2014_000000458338	adversarial
29	30	Is there a truck in the image?	no	COCO_val2014_000000458338	adversarial
30	31	Is there a dog in the image?	yes	COCO_val2014_000000283412	adversarial
31	32	Is there a person in the image?	no	COCO_val2014_000000283412	adversarial
32	33	Is there a dining table in the image?	yes	COCO_val2014_000000283412	adversarial
33	34	Is there a chair in the image?	no	COCO_val2014_000000283412	adversarial
34	35	Is there a bed in the image?	yes	COCO_val2014_000000283412	adversarial
35	36	Is there a book in the image?	no	COCO_val2014_000000283412	adversarial
36	37	Is there a person in the image?	yes	COCO_val2014_000000265719	adversarial
37	38	Is there a car in the image?	no	COCO_val2014_000000265719	adversarial
38	39	Is there a spoon in the image?	yes	COCO_val2014_000000265719	adversarial
39	40	Is there a cup in the image?	no	COCO_val2014_000000265719	adversarial
40	41	Is there a fork in the image?	yes	COCO_val2014_000000265719	adversarial
41	42	Is there a dining table in the image?	no	COCO_val2014_000000265719	adversarial
42	43	Is there a tv in the image?	yes	COCO_val2014_000000461331	adversarial
43	44	Is there a person in the image?	no	COCO_val2014_000000461331	adversarial
44	45	Is there a toaster in the image?	yes	COCO_val2014_000000461331	adversarial
45	46	Is there a book in the image?	no	COCO_val2014_000000461331	adversarial
46	47	Is there a microwave in the image?	yes	COCO_val2014_000000461331	adversarial
47	48	Is there a bottle in the image?	no	COCO_val2014_000000461331	adversarial
48	49	Is there a backpack in the image?	yes	COCO_val2014_000000544456	adversarial
49	50	Is there a handbag in the image?	no	COCO_val2014_000000544456	adversarial
50	51	Is there a person in the image?	yes	COCO_val2014_000000544456	adversarial
51	52	Is there a car in the image?	no	COCO_val2014_000000544456	adversarial
52	53	Is there a skis in the image?	yes	COCO_val2014_000000544456	adversarial
53	54	Is there a snowboard in the image?	no	COCO_val2014_000000544456	adversarial
54	55	Is there a bird in the image?	yes	COCO_val2014_000000017708	adversarial
55	56	Is there a handbag in the image?	no	COCO_val2014_000000017708	adversarial
56	57	Is there a person in the image?	yes	COCO_val2014_000000017708	adversarial
57	58	Is there a car in the image?	no	COCO_val2014_000000017708	adversarial
58	59	Is there a boat in the image?	yes	COCO_val2014_000000017708	adversarial
59	60	Is there a chair in the image?	no	COCO_val2014_000000017708	adversarial
60	61	Is there a person in the image?	yes	COCO_val2014_000000574692	adversarial
61	62	Is there a car in the image?	no	COCO_val2014_000000574692	adversarial
62	63	Is there an orange in the imange?	yes	COCO_val2014_000000574692	adversarial
63	64	Is there a dining table in the image?	no	COCO_val2014_000000574692	adversarial
64	65	Is there a bottle in the image?	yes	COCO_val2014_000000574692	adversarial
65	66	Is there a cup in the image?	no	COCO_val2014_000000574692	adversarial
66	67	Is there a backpack in the image?	yes	COCO_val2014_000000353180	adversarial
67	68	Is there a handbag in the image?	no	COCO_val2014_000000353180	adversarial
68	69	Is there a person in the image?	yes	COCO_val2014_000000353180	adversarial
69	70	Is there a car in the image?	no	COCO_val2014_000000353180	adversarial
70	71	Is there a bus in the image?	yes	COCO_val2014_000000353180	adversarial
71	72	Is there a traffic light in the image?	no	COCO_val2014_000000353180	adversarial
72	73	Is there a person in the image?	yes	COCO_val2014_000000239444	adversarial
73	74	Is there a car in the image?	no	COCO_val2014_000000239444	adversarial
74	75	Is there a dining table in the image?	yes	COCO_val2014_000000239444	adversarial
75	76	Is there a cup in the image?	no	COCO_val2014_000000239444	adversarial
76	77	Is there a chair in the image?	yes	COCO_val2014_000000239444	adversarial
77	78	Is there a couch in the image?	no	COCO_val2014_000000239444	adversarial
78	79	Is there a person in the image?	yes	COCO_val2014_000000569839	adversarial
79	80	Is there a car in the image?	no	COCO_val2014_000000569839	adversarial
80	81	Is there a sandwich in the image?	yes	COCO_val2014_000000569839	adversarial
81	82	Is there a bowl in the image?	no	COCO_val2014_000000569839	adversarial
82	83	Is there a hot dog in the image?	yes	COCO_val2014_000000569839	adversarial
83	84	Is there a handbag in the image?	no	COCO_val2014_000000569839	adversarial
84	85	Is there a person in the image?	yes	COCO_val2014_000000219622	adversarial
85	86	Is there a dining table in the image?	no	COCO_val2014_000000219622	adversarial
86	87	Is there a car in the image?	yes	COCO_val2014_000000219622	adversarial
87	88	Is there a truck in the image?	no	COCO_val2014_000000219622	adversarial
88	89	Is there a frisbee in the image?	yes	COCO_val2014_000000219622	adversarial
89	90	Is there a dog in the image?	no	COCO_val2014_000000219622	adversarial
90	91	Is there a knife in the image?	yes	COCO_val2014_000000300368	adversarial
91	92	Is there a cup in the image?	no	COCO_val2014_000000300368	adversarial
92	93	Is there a person in the image?	yes	COCO_val2014_000000300368	adversarial
93	94	Is there a car in the image?	no	COCO_val2014_000000300368	adversarial
94	95	Is there a cake in the image?	yes	COCO_val2014_000000300368	adversarial
95	96	Is there a bottle in the image?	no	COCO_val2014_000000300368	adversarial
96	97	Is there a person in the image?	yes	COCO_val2014_000000482476	adversarial
97	98	Is there a car in the image?	no	COCO_val2014_000000482476	adversarial
98	99	Is there a remote in the image?	yes	COCO_val2014_000000482476	adversarial
99	100	Is there a tv in the image?	no	COCO_val2014_000000482476	adversarial

End of preview. Expand in Data Studio

Large-scale Multi-modality Models Evaluation Suite

Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval

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This Dataset

This is a formatted version of POPE. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.

@article{li2023evaluating,
  title={Evaluating object hallucination in large vision-language models},
  author={Li, Yifan and Du, Yifan and Zhou, Kun and Wang, Jinpeng and Zhao, Wayne Xin and Wen, Ji-Rong},
  journal={arXiv preprint arXiv:2305.10355},
  year={2023}
}

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Collection including lmms-lab/POPE

LMMs-Eval

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Dataset Collection of LMMs-Eval • 36 items • Updated Oct 4, 2024 • 29