Image Classification on ImageNet and 10 Target Datasets (zero-shot) benchmark leaderboard · SOTA2 Research

Image Classification on ImageNet and 10 Target Datasets (zero-shot)

72.03ImageNet Accuracy (zero-shot)MMRL

Evaluation Results

Method	Links
MMRL2026.05		72.03	94.67	91.43	66.1	72.77	86.4	26.3	67.57	45.9	53.1	68.27	67.25	1.69
MMRL++2026.05		71.87	94.63	91.43	66.6	73.53	86.73	26.07	67.77	46.13	53	69.03	67.49	1.93
CoOp2026.05		71.51	93.7	89.14	64.51	68.71	85.3	18.47	64.15	41.92	46.39	66.55	63.88	1.68
TCP2026.05		71.4	93.97	91.25	64.69	71.21	86.69	23.45	67.15	44.35	51.45	68.73	66.29	0.73
PromptSRC2026.05		71.27	93.6	90.25	65.7	70.25	86.15	23.9	67.1	46.87	45.5	68.75	65.81	0.25
CoCoOp2026.05		71.02	94.43	90.14	65.32	71.88	86.06	22.94	67.36	45.73	45.37	68.21	65.74	0.18
MMAC2026.05		71	93.8	90.3	66.13	72.07	86.12	25.33	68.17	46.57	49.24	68.32	66.61	1.05
MaPLe2026.05		70.72	93.53	90.49	65.57	72.23	86.2	24.74	67.01	46.49	48.06	68.69	66.3	0.74
KgCoOp2026.05		70.66	93.7	89.83	65.41	70.01	86.36	22.51	66.16	46.35	46.04	68.5	65.96	0.4
PERL2026.05		70.25	94.33	90.36	66.92	70.79	86.37	24.6	67.46	45.72	40.01	69.05	65.56	—