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Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network
Learning effective representations of entities and relations for knowledge graphs (KGs) is critical to the success of many …
Guanzheng Chen, Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, Shangsong Liang
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Learning Robust Recommenders through Cross-Model Agreement
Learning from implicit feedback is one of the most common cases in the application of recommender systems. Generally speaking, …
Yu Wang, Xin Xin, Zaiqiao Meng, Joemon M Jose, Fuli Feng, Xiangnan He
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Meta-Learning Helps Personalized Product Search
Personalized product search that provides users with customized search services is an important task for e-commerce platforms. This …
Bin Wu, Zaiqiao Meng, Qiang Zhang, Shangsong Liang
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Revisiting Parameter-Efficient Tuning: Are We Really There Yet?
Parameter-efficient tuning (PETuning) methods have been deemed by many as the new paradigm for using pretrained language models (PLMs). …
Guanzheng Chen, Fangyu Liu, Zaiqiao Meng, Shangsong Liang
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Revisiting Parameter-Efficient Tuning: Are We Really There Yet?
Hyperspherical Variational Co-embedding for Attributed Networks
Network-based information has been widely explored and exploited in the information retrieval literature. Attributed networks, …
Jinyuan Fang, Shangsong Liang, Zaiqiao Meng, Maarten De Rijke
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Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models
Knowledge probing is crucial for understanding the knowledge transfer mechanism behind the pre-trained language models (PLMs). Despite …
Zaiqiao Meng, Fangyu Liu, Ehsan Shareghi, Yixuan Su, Charlotte Collins, Nigel Collier
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Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models
Structure-Aware Random Fourier Kernel for Graphs
Gaussian Processes (GPs) define distributions over functions and their generalization capabilities depend heavily on the choice of …
Jinyuan Fang, Qiang Zhang, Zaiqiao Meng, Shangsong Liang
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Variational Bayesian representation learning for grocery recommendation
Representation learning has been widely applied in real-world recommendation systems to capture the features of both users and items. …
Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis
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Variational Continual Bayesian Meta-Learning
Conventional meta-learning considers a set of tasks from a stationary distribution. In contrast, this paper focuses on a more complex …
Qiang Zhang, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang, Emine Yilmaz
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TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
Masked language models (MLMs) such as BERT and RoBERTa have revolutionized the field of Natural Language Understanding in the past few …
Yixuan Su, Fangyu Liu, Zaiqiao Meng, Tian Lan, Lei Shu, Ehsan Shareghi, Nigel Collier
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