149 citations · 218 across the 53 of their papers we have counts for
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Disentangled Contrastive Learning for Zero-Shot Multilingual Dense Retrieval
Chao Huang, Yufeng Chen, Changhao Guan +3
Multilingual dense retrieval aims to handle queries and documents across different languages based on a unified retriever model. The challenge lies in enabling robust retrieval tra…
CroSearch-R1: Better Leveraging Cross-lingual Knowledge for Retrieval-Augmented Generation
Rui Qi, Fengran Mo, Sijin Lu +3
A multilingual collection may contain useful knowledge in other languages to supplement and correct the facts in the original language for Retrieval-Augmented Generation (RAG). How…
KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models
Songming Zhang, Xue Zhang, Tong Zhang +3
Knowledge distillation (KD) is widely used to compress and post-train large language models (LLMs), yet many existing frameworks execute teacher inference with the same training-or…
Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation
Rui Qi, Fengran Mo, Yufeng Chen +6
Multilingual retrieval-augmented generation (MRAG) requires models to effectively acquire and integrate beneficial external knowledge from multilingual collections. However, most e…