189 citations · 453 across the 62 of their papers we have counts for
4 papers · 1 filter
Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate Pairs
Cheng Gao, Chaojun Xiao, Zhenghao Liu +3
Legal case retrieval (LCR) aims to provide similar cases as references for a given fact description. This task is crucial for promoting consistent judgments in similar cases, effec…
Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language
Zekai Qu, Ruobing Xie, Chaojun Xiao +5
With the thriving of pre-trained language model (PLM) widely verified in various of NLP tasks, pioneer efforts attempt to explore the possible cooperation of the general textual in…
UPRec: User-Aware Pre-training for Recommender Systems
Chaojun Xiao, Ruobing Xie, Yuan Yao +4
Existing sequential recommendation methods rely on large amounts of training data and usually suffer from the data sparsity problem. To tackle this, the pre-training mechanism has…
Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect
Zheni Zeng, Chaojun Xiao, Yuan Yao +5
Recommender systems aim to provide item recommendations for users, and are usually faced with data sparsity problem (e.g., cold start) in real-world scenarios. Recently pre-trained…