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
2022Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval34 citationsDOIOpen Access PDF
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.
Topics & Concepts
Computer scienceTask (project management)Natural language processingLanguage modelInformation retrievalArtificial intelligenceQuestion answeringData retrievalManagementEconomicsTopic ModelingMultimodal Machine Learning ApplicationsNatural Language Processing Techniques