13 citations · 26 across the 4 of their papers we have counts for
5 papers
Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective
Ying Zhou, Xuanang Chen, Ben He +2
Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph. Current KGC research mostly follows an entity ranking protocol,…
Groupwise Query Performance Prediction with BERT
Xiaoyang Chen, Ben He, Le Sun
While large-scale pre-trained language models like BERT have advanced the state-of-the-art in IR, its application in query performance prediction (QPP) is so far based on pointwise…
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision
Ning Bian, Xianpei Han, Bo Chen +3
Despite recent success in machine reading comprehension (MRC), learning high-quality MRC models still requires large-scale labeled training data, even using strong pre-trained lang…
Co-BERT: A Context-Aware BERT Retrieval Model Incorporating Local and Query-specific Context
Xiaoyang Chen, Kai Hui, Ben He +3
BERT-based text ranking models have dramatically advanced the state-of-the-art in ad-hoc retrieval, wherein most models tend to consider individual query-document pairs independent…
BERT-QE: Contextualized Query Expansion for Document Re-ranking
Zhi Zheng, Kai Hui, Ben He +3
Query expansion aims to mitigate the mismatch between the language used in a query and in a document. However, query expansion methods can suffer from introducing non-relevant info…