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arXiv · 2204.11989

C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval

Eugene Yang·Suraj Nair·Ramraj Chandradevan·Rebecca Iglesias-Flores·Douglas W. Oard
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Abstract

Pretrained language models have improved effectiveness on numerous tasks, including ad-hoc retrieval. Recent work has shown that continuing to pretrain a language model with auxiliary objectives before fine-tuning on the retrieval task can further improve retrieval effectiveness. Unlike monolingual retrieval, designing an appropriate auxiliary task for cross-language mappings is challenging. To address this challenge, we use comparable Wikipedia articles in different languages to further pretrain off-the-shelf multilingual pretrained models before fine-tuning on the retrieval task. We show that our approach yields improvements in retrieval effectiveness.

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Eugene Yang, Suraj Nair, Ramraj Chandradevan, Rebecca Iglesias-Flores, Douglas W. Oard. 2022-04-25. C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval. https://doi.org/10.1145/3477495.3531886

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