416 citations · 1k across the 56 of their papers we have counts for
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Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval
Ning Wu, Yaobo Liang, Houxing Ren +4
Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a sim…
Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation
Shengyao Zhuang, Houxing Ren, Linjun Shou +4
The Differentiable Search Index (DSI) is an emerging paradigm for information retrieval. Unlike traditional retrieval architectures where index and retrieval are two different and…
Negative Sampling for Contrastive Representation Learning: A Review
Lanling Xu, Jianxun Lian, Wayne Xin Zhao +5
The learn-to-compare paradigm of contrastive representation learning (CRL), which compares positive samples with negative ones for representation learning, has achieved great succe…
Label-aware Multi-level Contrastive Learning for Cross-lingual Spoken Language Understanding
Shining Liang, Linjun Shou, Jian Pei +4
Despite the great success of spoken language understanding (SLU) in high-resource languages, it remains challenging in low-resource languages mainly due to the lack of labeled trai…
Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling
Nuo Chen, Linjun Shou, Ming Gong +2
Large-scale cross-lingual pre-trained language models (xPLMs) have shown effectiveness in cross-lingual sequence labeling tasks (xSL), such as cross-lingual machine reading compreh…
Transformer-Empowered Content-Aware Collaborative Filtering
Weizhe Lin, Linjun Shou, Ming Gong +4
Knowledge graph (KG) based Collaborative Filtering is an effective approach to personalizing recommendation systems for relatively static domains such as movies and books, by lever…