5. 🤖 Despite high correlations at the language level, we find that x-ling alignment metrics do not differ between samples LLM answers correctly in En and XX (EC-XC) and samples LLM answers correctly in En and wrongly in XX (EC-XW) for 2/3 NLU tasks.

3. 🔍 Alignment at an aggregate level: x-ling alignment (i.e., the percentage of aligned samples) for a given language correlates with accuracy across three NLU tasks. Also, we find x-ling alignment correlates with En-XX translation quality (r=0.87 in FLORES) over XX-En (0.68)

2. We introduce novel measures of x-ling alignment by extracting the embeddings of parallel XX and En text across the layers of the transformer: Discriminative Alignment Index (DALI) and its stronger variant (DALI.S)

Every day keeps getting shorter never seem to find the time 🎶