Image Classification on CIFAR-10N ResNet-18 (test)

95.6Clean AccuracyFull-training

Evaluation Results

Method
Full-training2026.04	95.6	90.7	78.3	91.3	85.4	65.6	90.6	85.8	—
DUAL2026.04	95.5	90.1	80.4	91.7	79.2	40.2	87.1	67.8	-6.4
Dyn-Unc2026.04	95.4	89.3	78.8	90.9	84.5	47.1	80.7	71.2	-5.7
DUAL2026.04	95.4	90.1	81.3	92	83.6	41.8	89	75.3	-4.3
Dyn-Unc2026.04	95.3	89.6	78.7	89.6	78.6	44.8	82.6	76.1	-6
DivBS2026.04	95.3	90.3	78.3	85.3	79.2	50.3	88	82.8	-4.2
InfoBatch2026.04	95.3	91	78.1	92	85.6	67.5	91.3	87	0.5
InfoBatch + Ours2026.04	95.3	91.4	82	92.7	87.9	67.8	92.9	90	2.1
SeTa + Ours2026.04	95.3	90.7	79.1	92.5	85	64.6	91.8	89.3	0.6
SeTa2026.04	95.2	90.6	76.3	91.8	84.7	64.2	90.8	88.4	-0.2
IES2026.04	95	89.8	79.8	87.5	80	46	88.9	82.3	-4.3
IES2026.04	95	89.8	78.6	87	79.1	35.7	88.5	78.3	-6.4
InfoBatch2026.04	95	90.5	77.7	92	87.5	64.3	92	87.5	0.4
InfoBatch + Ours2026.04	95	91.3	82.4	92.8	87.6	64.5	92.1	89.8	1.5
DivBS2026.04	94.9	89.8	78	85.9	79.6	48.6	88.8	84.6	-4.2
SeTa + Ours2026.04	94.9	89.7	79.3	91.9	87.6	60.2	92.2	88.5	0.1
Dynamic Random2026.04	94.8	90.3	77.3	90.8	84.2	64.8	91.5	84.5	-0.6
SeTa2026.04	94.8	89.4	78.5	91.3	86	53	91.7	87.9	-1.4
DivBS2026.04	94.8	89.8	79.8	86.2	80.3	48.5	90	83.8	-3.8
Static Random2026.04	94.6	89.9	75	89	81.2	57.6	87.9	82.5	-3.2
Margin2026.04	94.5	88.9	64.6	85.4	15	12	79.8	47.6	-24.4
Dynamic Random2026.04	94.5	89.2	76.1	88.9	83.7	63.3	90.6	83.7	-1.7
IES2026.04	94.5	89	76.7	86.1	74.6	35.4	87.6	73.3	-8.3
SeTa + Ours2026.04	94.5	90	79.4	92.6	87.7	58	92.5	88.5	0
InfoBatch2026.04	94.3	89.9	79.4	92.4	87	61	92.5	88.3	0.2
InfoBatch + Ours2026.04	94.3	90.8	81	92.8	87.9	61.1	92.9	89.2	0.8
SeTa2026.04	94.3	89.5	77.7	92.2	87.1	30.4	92.2	88.1	-4
GraNd2026.04	93.9	87.8	40.5	65.9	17.5	11	60.5	38.7	-33.4
Forget2026.04	93.6	89.5	69.6	84.5	59	22.5	80.5	58.3	-15.7
DUAL2026.04	93.5	90.3	80.4	91.7	86.6	45.2	90.8	75.2	-3.7
SSP2026.04	93.4	88.6	66	83.4	53.1	16.6	80.3	59.5	-17.8
Static Random2026.04	93.3	88.6	72.4	87.4	77.5	51.4	85.8	77.9	-6.1
Margin2026.04	93.3	85.2	44.6	70.7	13.5	10.7	57.5	38.6	-33.7
Glister2026.04	93.1	88.7	75.6	83.8	73.1	37.1	84.1	74.3	-9.2
Prune4ReL†2026.04	93	88.3	66.1	81.8	52.2	15.8	81.1	59	-18.3
Dynamic Random2026.04	93	87.4	75.9	87.4	84.6	60.2	91.4	86.8	-2.1
Forget2026.04	92.4	88.4	72.2	85.7	68.3	29.8	79.9	57.4	-13.7
Dyn-Unc2026.04	92.2	86.3	79.6	90.1	86.8	47.2	81.9	71.4	-6
Moderate2026.04	92.1	89.9	66.8	87.8	52.8	17.8	80.8	58.3	-17.1
Prune4ReL†2026.04	91.6	85.9	63.9	78.4	49.6	16.3	78.8	56.7	-20.3
SSP2026.04	91.5	87.1	65.8	81.2	50.7	16.3	79.4	58.6	-19.1
Glister2026.04	91.4	86.8	71.8	80.2	67.9	32.8	80.9	71.5	-12.5
GraNd2026.04	91.2	78.6	21	39.2	7.1	6.9	37.2	32.3	-46.2
Margin2026.04	91.2	71.7	15.1	22.6	12.3	9.8	34	27.3	-49.9
Moderate2026.04	90.8	88.2	66.9	89.9	48.8	17.4	80.1	57.7	-17.9
Static Random2026.04	90.2	86.6	69	85.3	73.8	41.4	82.3	75.3	-9.9
Forget2026.04	89.8	86.2	70.9	85.5	71.5	33	78.4	55.2	-14.1
SmallL2026.04	88.9	87.2	78.2	89.3	72.1	24	87.4	68.9	-10.9
Glister2026.04	88.5	83.7	65.1	75	58.3	37.1	75.3	64.7	-17
Prune4ReL†2026.04	88.4	82.2	59.7	73.3	43.5	16.2	74.2	56.1	-23.7
Moderate2026.04	87.8	84.8	66.3	87.3	47.8	16.7	77.7	55.4	-19.9
SSP2026.04	87.8	82	60.5	73.9	41.2	15.8	74.7	55.1	-24
SmallL2026.04	84.1	84.1	78	84.7	80.8	30.9	84.7	60.9	-11.9
GraNd2026.04	78.1	52.1	10.2	14.3	8.2	7.8	18.9	28.5	-58.1
SmallL2026.04	75.1	76.3	74.4	78.2	76.1	35.4	73.1	62.7	-16.5