Image Classification on ImageNet and 10 Target Datasets (test) benchmark leaderboard · SOTA2 Research

Image Classification on ImageNet and 10 Target Datasets (test)

73.7ImageNet AccuracyMMRL

Evaluation Results

Method	Links
MMRL2025.12		73.7	66.13	94.43	91.3	64.67	71.87	85.1	25.37	67	44.03	48.6	68.93
FARL2025.12		73.43	66.84	94.53	91.7	66.07	72.47	86.07	25.97	67.53	44.6	50.67	68.83
TCP2025.12		71.4	66.29	93.97	91.25	64.69	71.21	86.69	23.45	67.15	44.35	51.45	68.73
CoOp2025.12		71.02	65.74	94.43	90.14	65.32	71.88	86.06	22.94	67.36	45.73	45.37	68.21
MMA2025.12		71	66.61	93.8	90.3	66.13	72.07	86.12	25.33	68.17	46.57	49.24	68.32
MMRL + ReBaPL2025.11		71	67.62	94.6	91.97	66.63	72.57	86.43	26.33	67.9	47.27	52.97	69.5
MaPLe2025.12		70.72	66.3	93.53	90.49	65.57	72.23	86.2	24.74	67.01	46.49	48.06	68.69
MMRL*2025.11		70.13	66.87	94.3	91	66.2	71.53	86.2	26.07	67.5	46.93	49.83	69.13
PromptSRC*2025.11		68.96	65.5	93.47	90.33	65.87	70.4	83.66	24.13	67.17	46.4	45.97	67.67
MaPLe + ReBaPL2025.11		68.66	66.77	93.8	90.73	66.3	72.57	86.4	24.37	67.7	47.17	50.9	67.87
MaPLe*2025.11		67.96	65.63	93.17	90.2	65.97	71.07	86.33	23.23	67.23	47.2	45.7	66.27