
doi: 10.5281/zenodo.21518774 , 10.5281/zenodo.21518775 , 10.5281/zenodo.21249485 , 10.5281/zenodo.21542697 , 10.5281/zenodo.21581029 , 10.5281/zenodo.21518823 , 10.5281/zenodo.21490846 , 10.5281/zenodo.21330965 , 10.5281/zenodo.21518824 , 10.5281/zenodo.21581028 , 10.5281/zenodo.21542696 , 10.5281/zenodo.21330966 , 10.5281/zenodo.21249484 , 10.5281/zenodo.21552609 , 10.5281/zenodo.21490845 , 10.5281/zenodo.21552608
doi: 10.5281/zenodo.21518774 , 10.5281/zenodo.21518775 , 10.5281/zenodo.21249485 , 10.5281/zenodo.21542697 , 10.5281/zenodo.21581029 , 10.5281/zenodo.21518823 , 10.5281/zenodo.21490846 , 10.5281/zenodo.21330965 , 10.5281/zenodo.21518824 , 10.5281/zenodo.21581028 , 10.5281/zenodo.21542696 , 10.5281/zenodo.21330966 , 10.5281/zenodo.21249484 , 10.5281/zenodo.21552609 , 10.5281/zenodo.21490845 , 10.5281/zenodo.21552608
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 model inference efficiency (measured in tokens per second) when applied to zero-shot cross-lingual tasks in XTREME-R, compared to direct fine-tuning without intermediate tasks? Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 9.2/10.
This report was generated autonomously by Assignee Research, an owner-gated autonomous research lab. The content synthesizes findings from peer-reviewed papers. Tribunal score: 9.2/10.
English-only, NLI, per, zero-shot, English, logical, tasks, latency, throughput, inference, training, model, effect, datasets, during, intermediate-task, downstream, improve, affect, efficiency, tokens, impact, measured, multilingual
English-only, NLI, per, zero-shot, English, logical, tasks, latency, throughput, inference, training, model, effect, datasets, during, intermediate-task, downstream, improve, affect, efficiency, tokens, impact, measured, multilingual
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