Active Learning on Multiple Datasets (test) benchmark leaderboard · SOTA2 Research

Active Learning on Multiple Datasets (test)

58.82AULCrandom

Evaluation Results

Method	Links
random2026.05		58.82	0.5934
TDS-Segment2026.05		58.78	0.5905
Core Set2026.05		58.78	0.5923
Exp. Model Change2026.05		58.78	0.5937
Uncert. Least Conf.2026.05		58.78	0.5938
Uncert. Res.2026.05		58.78	0.5938
Query By Comm.2026.05		58.77	0.5927
Uncert. Entropy2026.05		58.77	0.5936
Learning Loss2026.05		58.75	0.5932
BADGE2026.05		58.73	0.5923
TDS2026.05		58.65	0.5896
random2026.05		57.94	0.5853
Core Set2026.05		57.89	0.5851
Uncert. Entropy2026.05		57.86	0.5844
Exp. Model Change2026.05		57.86	0.5844
Uncert. Least Conf.2026.05		57.86	0.5845
Uncert. Res.2026.05		57.86	0.5845
BADGE2026.05		57.86	0.5847
Query By Comm.2026.05		57.86	0.5849
TDS-Segment2026.05		57.86	0.5873
Learning Loss2026.05		57.82	0.5855
TDS2026.05		57.78	0.5815
random2026.05		56.1	0.5672
TDS-Segment2026.05		56	0.5724
Query By Comm.2026.05		55.99	0.5668
Core Set2026.05		55.99	0.5674
Uncert. Entropy2026.05		55.93	0.5664
Exp. Model Change2026.05		55.93	0.5664
Uncert. Least Conf.2026.05		55.9	0.5667
Uncert. Res.2026.05		55.9	0.5667
BADGE2026.05		55.89	0.568
Learning Loss2026.05		55.85	0.5665
TDS2026.05		55.82	0.5655