This research focuses on overcoming the language barriers in recommendation systems by using Transformer Leveraged Document Representations (TLDRs) to represent documents across languages. The team evaluated four multilingual pre-trained transformer models using three mapping methods across 20 language pairs. The results show that mapped TLDRs are effective in creating cross-lingual representations, suggesting a promising direction for expanding beyond language connections.
Publication date: 15 Jan 2024
Project Page: [email protected], [email protected], [email protected], [email protected]
Paper: https://arxiv.org/pdf/2401.06583
