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Lifelong Learning on SST, QA-SRL, and WOZ Permuted Sequences GPT-2 models (test)

82.4Accuracy (SRL WOZ SST)

LSEBMCL

Updated 1mo ago

Evaluation Results

Method	Links
LSEBMCL 2025.12		82.4	83.1	82.5	82.7	83.7	83.2	82.9	0.5
PPSEBM 2025.12		82.2	83.4	84	82.2	85.5	83.3	83.4	1.2
RVAE-LAMOL 2025.12		82	81.5	82.3	81.5	81.1	82.8	81.9	0.6
LSEBMCL 2025.12		81.9	82.8	81.8	84.4	82.7	80.5	82.4	1.3
Multitasked 2019.09		81.5	-	-	-	-	-	-	-
LAMOL REAL 2019.09		81.2	81.8	80.6	81.6	80.4	80.5	81	0.5
LAMOL REAL 2019.09		80.9	81	78.9	80.1	77.7	78	79.4	1.2
PPSEBM 2025.12		80.9	82.8	83.7	82.1	85.2	83	83	1.4
LAMOL 2025.12		80.3	80.8	81.1	81.2	78.9	81.9	80.7	1
RVAE-LAMOL 2025.12		80.2	80.7	79.6	79.9	79.6	78	79.7	0.9
LAMOL GEN 2019.09		78.7	80	80.7	79.6	78.4	80.5	79.7	0.8
LAMOL TASK 2019.09		78.7	79.4	79.9	80.1	79.8	79	79.5	0.5
LAMOL TASK 2019.09		74.7	77.3	76.9	78.1	73.4	75.8	76	1.5
LAMOL GEN 2019.09		73.7	79.6	78.9	73.1	68.6	75.7	74.9	3.4
LAMOL 2025.12		73.7	81.5	79.5	74.8	70.2	75.8	75.9	4.1
LSEBMCL 2025.12		66.8	66.4	57.7	77.7	64.6	65.6	66.5	6.4
PPSEBM 2025.12		62.8	78.7	54.6	75.6	61.4	61.6	65.8	9.3
LAMOL TASK 2019.09		41.9	41	33.5	50.1	49.3	41.5	42.9	5.2
LAMOL 2025.12		39.4	47.1	38.4	57.8	45.5	46.6	45.8	7
LAMOL GEN 2019.09		38.6	46.5	36.6	56.6	44.9	45.2	44.8	6
EWC 2025.12		37.5	51	50	66.4	44.8	40.7	48.4	10.2
EWC 2019.09		35.5	50.6	48.4	64.7	43.9	39	47	8.7
Fine-tuned 2025.12		33.2	52	25.5	64.6	34.6	34.6	40.8	14.6
GEM 2025.12		32.9	52.1	31.5	64	45.3	36.7	43.8	12.6
GEM 2019.09		32.6	50.4	29.8	63.3	44.1	36.3	42.8	11
MAS 2025.12		32.3	37.3	46.2	57.3	50.3	32.2	42.6	10.3
Fine-tuned 2019.09		31.3	50.2	24.7	62.9	32.8	33.9	39.3	12
MAS 2019.09		31	36.5	45.3	56.6	49.7	30.8	41.6	8.9
Multitasked 2025.12		-	-	-	-	-	-	87	-