Publication | Open Access
C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval
34
Citations
11
References
2022
Year
Natural Language ProcessingRetrieval EffectivenessRetrieval Augmented GenerationEngineeringMachine LearningInformation RetrievalLlm Fine-tuningCross-lingual RepresentationContrastive Weak SupervisionComputational LinguisticsMonolingual RetrievalCross-language RetrievalPre-trained ModelsLanguage StudiesMultilingual PretrainingLinguisticsText MiningMachine Translation
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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