
doi: 10.5281/zenodo.21230071 , 10.5281/zenodo.21449223 , 10.5281/zenodo.21312521 , 10.5281/zenodo.21230072 , 10.5281/zenodo.21409269 , 10.5281/zenodo.21453530 , 10.5281/zenodo.21449224 , 10.5281/zenodo.21453529 , 10.5281/zenodo.21613270 , 10.5281/zenodo.21409268 , 10.5281/zenodo.21371123 , 10.5281/zenodo.21371122 , 10.5281/zenodo.21613269 , 10.5281/zenodo.21312520
doi: 10.5281/zenodo.21230071 , 10.5281/zenodo.21449223 , 10.5281/zenodo.21312521 , 10.5281/zenodo.21230072 , 10.5281/zenodo.21409269 , 10.5281/zenodo.21453530 , 10.5281/zenodo.21449224 , 10.5281/zenodo.21453529 , 10.5281/zenodo.21613270 , 10.5281/zenodo.21409268 , 10.5281/zenodo.21371123 , 10.5281/zenodo.21371122 , 10.5281/zenodo.21613269 , 10.5281/zenodo.21312520
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: How does multilingual intermediate-task training in non-English languages compare to English-only training in improving zero-shot cross-lingual performance on the XTREME-R benchmark? Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.5/10.
This report was generated autonomously by Assignee Research, an owner-gated autonomous research lab. The content synthesizes findings from peer-reviewed papers. Tribunal score: 8.5/10.
mT5, English-only, languages, task, XTREME-ML, corpora, models, zero-shot, parallel, high-resource, intermediate, benchmarks, non-English, tasks, set, XLM-R, training, like, intermediate-task, improve, incorporating, improving, XQuAD, diverse, multilingual
mT5, English-only, languages, task, XTREME-ML, corpora, models, zero-shot, parallel, high-resource, intermediate, benchmarks, non-English, tasks, set, XLM-R, training, like, intermediate-task, improve, incorporating, improving, XQuAD, diverse, multilingual
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