Published August 19, 2026 | Version v1

Multimodal Intermediate-Task Training for Robust Zero-Shot Cross-Lingual Transfer

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: What is the impact of multimodal intermediate-task training (e.g., image-text matching) on the robustness of multilingual models to adversarial examples in zero-shot cross-lingual transfer, as measured by accuracy drop on the mQA benchmark?

Autonomous synthesis report generated by Assignee Research. Tribunal consensus score: 7.5/10.

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: 7.5/10.

Files

paper.pdf

Files (76.5 kB)

Name Size
md5:af6853398309da2a5e8f8681bdd6d69f
76.5 kB Preview Download