Accuracy Trade-off Analysis of LLaVA and BLIP-2 in Zero-Shot Cross-Lingual Evaluation on XTREME-R

Intermediate-task training---fine-tuning a pretrained model on an intermediate task before fine-tuning again on the target task---often improves model performance substantially on language understanding tasks in monolingual English settings. We investigate whether English intermediate-task training is still helpful on non-English target tasks. Using nine intermediate language-understanding tasks, we evaluate intermediate-task transfer in a zero-shot cross-lingual setting on the XTREME benchmark. We see large improvements from intermediate training on the BUCC and Tatoeba sentence retrieval tas

Research goal: What is the accuracy trade-off between LLaVA and BLIP-2 when applying English intermediate-task training for zero-shot cross-lingual evaluation on the XTREME-R benchmark, measured using F1 scores across different language families?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.0/10.