Table 1: Micro F1 scores of different models in the node classification task. The column "A.R." reports the average rank of each model. Asterisk (*) denotes the best result on each dataset, and bold numbers denote the best result among graph pre-training models in the freezing or fine-tuning setting. The notation  $/$  means out of memory or no convergence for more than three days.
Dataset Method	brazil	dd242	dd68	dd687	wisconsin	cornell	cora	pubmed	ogbarxiv	ogbproteins	A.R.
Random	32.16(13.65)	6.71(2.44)	8.29(4.35)	5.98(2.70)	26.79(8.59)	39.77(7.26)	26.80(1.62)	38.85(0.76)	11.89(4.66)	52.69(5.94)	13.2
ProNE	50.24(11.56)	10.04(2.56)	7.73(3.11)	3.88(1.66)	44.67(7.49)	47.32(12.14)	80.76(2.92)*	78.80(0.98)*	65.96(0.06)*	76.28(0.34)*	7.5
DeepWalk	43.16(16.78)	8.11(1.45)	6.72(3.04)	6.17(2.18)	39.61(9.11)	47.67(8.30)	49.85(9.26)	44.99(10.89)	16.04(2.98)	64.74(0.49)	8.7
struc2vec	25.54(11.74)	13.71(2.66)	10.30(3.23)	7.98(2.74)	45.39(7.36)	38.39(9.18)	36.01(2.41)	44.45(0.78)	/	/	10.6
DGI	56.44(7.79)	14.35(0.44)	13.57(0.44)	11.04(1.93)	49.46(5.46)	49.85(9.26)	30.02(0.44)	42.39(0.84)	12.93(7.67)	55.98(0.33)	6.6
GAE	57.88(10.68)	14.09(1.52)	13.43(0.96)	10.25(2.63)	45.78(4.18)	49.26(5.24)	30.10(0.31)	40.14(0.68)	/	/	8.5
GraphSAGE	67.93(9.28)	14.33(0.37)	13.55(0.70)	10.39(0.78)	47.03(1.98)	49.20(1.46)	35.93(1.76)	39.94(0.02)	/	/	7.1
GraphCL(freeze)	50.71(5.00)*	9.53(2.50)*	9.36(3.63)	6.03(1.86)	38.85(10.80)*	41.05(5.67)*	16.95(2.39)*	41.07(1.16)	/	/	12.2
JOAO (freeze)	71.22(7.21)	7.98(2.90)	12.36(2.59)	5.34(1.43)	42.69(8.15)	43.16(5.67)	18.13(2.82)	41.05(0.87)	/	/	10.9
GCC (freeze)	67.47(4.09)	15.83(0.80)	11.95(1.13)	9.61(0.94)	52.57(1.69)	46.87(1.73)	35.47(0.51)	46.40(0.18)	14.56(7.60)	59.15(0.35)	7.0
APT-G (freeze)	68.69(3.42)	17.21(1.13)	11.98(0.75)	9.54(1.29)	54.45(1.90)	46.53(1.59)	34.89(0.25)	46.49(0.22)	12.32(7.71)	60.38(0.41)	6.3
APT-P (freeze)	66.55(3.25)	16.58(0.97)	12.48(0.85)	10.33(0.83)	51.90(1.64)	47.33(2.31)	35.63(0.56)	46.16(0.12)	12.86(7.54)	60.32(0.32)	6.2
APT-R (freeze)	68.12(3.07)	16.72(0.72)	12.42(1.24)	11.05(0.88)	54.48(1.77)	46.80(1.08)	34.93(0.36)	46.02(0.11)	18.79(5.87)	62.18(0.46)	5.0
APT-L2 (freeze)	69.82(2.32)	16.79(0.88)	12.68(0.81)	10.34(1.12)	55.11(1.74)	48.76(2.20)	34.27(0.43)	46.21(0.15)	19.64(6.46)	60.23(0.37)	4.4
APT (freeze)	73.39(2.55)	16.57(0.94)	12.08(0.89)	10.35(1.24)	53.38(1.19)	47.37(1.29)	36.69(0.49)	46.88(0.21)	22.04(0.29)	62.29(0.55)	3.8
GraphCL (rand, fine-tune)	64.43(14.95)	15.04(0.85)	14.69(2.48)	10.99(0.58)	63.85(2.18)	44.21(10.58)	30.45(0.37)	40.73(0.66)	/	/	8.3
JOAO (rand, fine-tune)	72.14(6.74)	10.93(2.85)	8.08(2.15)	7.40(3.48)	45.38(13.30)	45.26(10.31)	29.93(2.84)	42.01(0.68)	/	/	9.6
GCC (rand, fine-tune)	58.51(3.07)	15.98(1.05)	13.16(1.06)	9.74(0.95)	53.85(2.58)	50.95(2.26)	43.70(0.52)	49.72(0.17)	18.61(1.88)	59.12(0.35)	7.6
GraphCL (fine-tune)	73.57(10.33)	15.35(0.99)	13.51(2.57)	10.66(1.04)	63.85(4.42)	51.05(2.41)	30.81(0.36)	42.91(0.91)	/	/	7.5
JOAO (fine-tune)	75.00(5.76)	10.54(3.07)	7.56(1.94)	8.77(2.39)	50.0(12.28)	42.11(10.26)	29.34(3.04)	42.21(0.88)	/	/	9.5
GCC (fine-tune)	74.46(3.05)	19.32(0.80)	13.87(1.13)	10.37(1.06)	59.47(1.49)	48.32(2.42)	43.34(0.38)	50.87(1.19)	18.62(1.92)	60.08(0.56)	6.4
APT-G (fine-tune)	77.60(1.48)	25.45(0.60)*	17.78(1.14)	11.27(0.76)	66.09(2.28)	53.02(1.51)	45.63(0.66)	50.81(0.18)	27.33(4.80)	60.02(0.32)	3.8
APT-P (fine-tune)	78.99(2.44)	25.19(0.87)	16.40(1.22)	11.69(1.19)	64.24(1.90)	50.05(1.39)	45.53(0.30)	50.66(0.18)	27.20(4.80)	59.86(0.32)	4.8
APT-R (fine-tune)	79.14(1.97)	24.96(0.57)	17.43(1.05)	11.29(1.04)	66.28(1.94)	53.56(2.28)*	46.02(0.83)	51.00(0.21)	18.41(1.84)	60.10(0.38)	3.4
APT-L2 (fine-tune)	78.75(1.63)	24.62(0.90)	17.83(1.35)*	12.26(0.78)*	67.04(1.50)*	52.94(1.95)	47.48(0.46)	51.25(0.21)	27.40(4.97)	60.85(0.46)	2.6
APT (fine-tune)	79.67(2.30)*	28.62(0.55)*	20.30(1.13)*	12.80(1.54)*	67.08(1.75)*	52.15(2.25)	47.51(0.62)	51.30(0.16)	27.40(4.87)	61.64(0.35)	1.3