C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval
This work addresses cross-language retrieval for multilingual applications, but it is incremental as it builds on existing pretraining methods.
The paper tackled the challenge of designing auxiliary tasks for cross-language ad-hoc retrieval by using comparable Wikipedia articles to continue pretraining multilingual models, resulting in improved retrieval effectiveness.
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.