Table 9.

Results over all MDLT benchmarks.

Algorithm	F1-Score (by domain)		Accuracy (by domain)		Accuracy (by shot)
	Average	Worst	Average	Worst	Many	Medium	Few	Zero
IRM	0.530	0.439	0.565	0.475	0.644	0.479	0.370	0.270
DANN	0.676	0.555	0.697	0.575	0.767	0.645	0.526	0.351
CDANN	0.657	0.543	0.682	0.562	0.769	0.590	0.499	0.341
CORAL	0.748	0.630	0.769	0.650	0.849	0.747	0.621	0.362
MMD	0.415	0.351	0.444	0.384	0.467	0.449	0.397	0.157
Focal	0.723	0.601	0.749	0.629	0.836	0.736	0.578	0.311
CBLoss	0.727	0.585	0.748	0.609	0.822	0.751	0.590	0.392
LDAM	0.732	0.590	0.756	0.612	0.842	0.745	0.577	0.333
Bsoftmax	0.765	0.648	0.779	0.664	0.826	0.803	0.688	0.476
CRT (2-stage training)	0.750	0.620	0.776	0.647	0.856	0.779	0.637	0.361
BoDA	0.741	0.619	0.765	0.644	0.853	0.739	0.617	0.351
BoDA (2-stage training)	0.764	0.652	0.786	0.674	0.858	0.787	0.676	0.382
ERM	0.719	0.588	0.748	0.618	0.844	0.719	0.539	0.372
GroupDRO	0.699	0.591	0.728	0.611	0.830	0.693	0.491	0.341
Mixup	0.734	0.601	0.755	0.625	0.843	0.722	0.563	0.368
SagNet	0.734	0.611	0.758	0.639	0.854	0.736	0.544	0.350
MLDG	0.724	0.586	0.752	0.613	0.846	0.726	0.576	0.352
MTL	0.719	0.585	0.746	0.613	0.840	0.720	0.563	0.350
Fish	0.717	0.587	0.748	0.616	0.845	0.726	0.570	0.354
BRL (ours)	0.774	0.681	0.784	0.691	0.828	0.794	0.705	0.497
BRL (2-stage training)	0.782	0.683	0.792	0.693	0.838	0.804	0.723	0.488