Partial Multi-Label Learning on birds (Average Precision) benchmark leaderboard · SOTA2 Research

Partial Multi-Label Learning on birds (Average Precision)

63.4Average PrecisionPML-MA

Evaluation Results

Method	Links
PML-MA2026.04		63.4
PML-PLR2026.04		63
WSC-PML2026.04		62.9
PML-ND2026.04		62.8
P-LENFN2026.04		62.7
PML-LENFN2026.04		62.7
NLR2026.04		62.6
FBD-PML2026.04		62.5
FBD-PML2026.04		62
PML-NI2026.04		61.7
PML-NI2026.04		61.7
PML-MA2026.04		59.9
PML-MA2026.04		59.7
WSC-PML2026.04		59.7
WSC-PML2026.04		59.2
PML-PLR2026.04		59
PML-ND2026.04		59
PAMB2026.04		58.9
PAMB2026.04		58.9
PML-PLR2026.04		58.5
PML-ND2026.04		58.5
P-LENFN2026.04		58.1
PML-LENFN2026.04		58.1
FBD-PML2026.04		58
FBD-PML2026.04		57.6
FBD-PML2026.04		57.5
NLR2026.04		57.5
PML-NI2026.04		57.2
PML-NI2026.04		57.2
P-LENFN2026.04		57
PML-LENFN2026.04		57
FBD-PML2026.04		56.8
PAMB2026.04		56.4
PML-NI2026.04		56.4
PAMB2026.04		56.4
PML-NI2026.04		56.4
NLR2026.04		55.8
PAMB2026.04		49.5
PAMB2026.04		49.5
PML-fp2026.04		45.7
PML-fp2026.04		45.7
PML-fp2026.04		42.4
PML-fp2026.04		42.4
PARTICLE2026.04		41.9
PML-fp2026.04		41.8
PML-fp2026.04		41.8
PARTICLE2026.04		37.9
PARTICLE2026.04		37.2