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A BLI Results for All 28 Language Pairs
VECMAP (supervised)	VECMAP (SL)	VECMAP (SL+R)	CLASSYMAP (SL)	CLASSYMAP (SL+R)
EN-DE	.238	.466	.392	.451	.460
EN-TR	.076	.247	.253	.273	.333
EN-FI	.081	.238	.203	.299	.350
EN-HR	.072	.213	.189	.238	.271
EN-RU	.135	.203	.222	.230	.266
EN-IT	.325	.552	.480	.542	.546
EN-FR	.314	.582	.536	.573	.580
DE-TR	.050	.207	.203	.221	.268
DE-FI	.070	.240	.194	.265	.297
DE-HR	.058	.229	.206	.246	.268
DE-RU	.111	.193	.208	.212	.239
DE-IT	.196	.464	.397	.475	.466
DE-FR	.143	.465	.426	.461	.484
TR-FI	.034	.200	.176	.217	.235
TR-HR	.030	.160	.171	.200	.227
TR-RU	.028	.123	.152	.162	.203
TR-IT	.061	.296	.290	.297	.334
TR-FR	.047	.307	.323	.316	.369
FI-HR	.049	.249	.195	.252	.278
FI-RU	.064	.263	.217	.280	.302
FI-IT	.066	.318	.317	.328	.376
FI-FR	.059	.322	.315	.330	.384
HR-RU	.076	.305	.265	.312	.347
HR-IT	.078	.366	.332	.361	.415
HR-FR	.053	.352	.325	.363	.411
RU-IT	.130	.402	.343	.409	.438
RU-FR	.106	.407	.370	.417	.442
IT-FR	.367	.633	.583	.630	.633
EN-X	.177	.357	.325	.372	.401
No EN	.089	.310	.286	.322	.353
All	.111	.321	.296	.334	.365
Table 5: P@1 BLI scores for all 28 language pairs. We report scores of 1) VECMAP in the supervised setting without self learning, 2) VECMAP and CLASSYMAP with only self learning but without reranking (SL), and 3) VECMAP and CLASSYMAP with both self learning and reranking  $(\mathrm{SL} + \mathrm{R})$ . All models start with the same seed set of 500 word translation pairs.