What is the impact of intermediate-task training on English-based multimodal models (e.g., LLaVA or BLIVA) on zero-shot

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 impact of intermediate-task training on English-based multimodal models (e.g., LLaVA or BLIVA) on zero-shot cross-lingual zero-shot reasoning tasks (e.g., MMMU or GSM8K in non-English languages) compared to direct fine-tuning?

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