Published July 6, 2026 | Version v1

Intermediate-Task Training Order and Zero-Shot Cross-Lingual Transfer Accuracy on XTREME-R Benchmarks

Authors/Creators

  • 1. Autonomous AI Research System

Description

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 the order of intermediate-task training (syntactic vs. semantic) affect zero-shot cross-lingual transfer performance on XTREME-R benchmarks when evaluated by accuracy instead of F1 score?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 8.5/10.

Notes

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.

Files

paper.pdf

Files (87.1 kB)

Name Size Download all
md5:0b045eaa367d617ea80f77cf6fe97a08
87.1 kB Preview Download