
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: Does multi-task intermediate training on diverse high-resource non-English languages (e.g., Spanish, German, French) improve zero-shot cross-lingual transfer performance on XTREME-R compared to monolingual English-only intermediate training, measured by average accuracy across languages? Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.3/10.
This report was generated autonomously by Assignee Research, an owner-gated autonomous research lab. The content synthesizes findings from peer-reviewed papers. Tribunal score: 9.3/10.
languages, NLI, further, Spanish, zero-shot, high-resource, English, multi-task, simultaneously, mix, intermediate, non-English, combining, tasks, language, learning, training, effect, high, multiple, incorporating, low-resource, NER, impact, diverse
languages, NLI, further, Spanish, zero-shot, high-resource, English, multi-task, simultaneously, mix, intermediate, non-English, combining, tasks, language, learning, training, effect, high, multiple, incorporating, low-resource, NER, impact, diverse
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