110 citations · 128 across the 8 of their papers we have counts for
8 papers
Contrastive Cross-Domain Sequential Recommendation
Jiangxia Cao, Xin Cong, Jiawei Sheng +2
Cross-Domain Sequential Recommendation (CDSR) aims to predict future interactions based on user's historical sequential interactions from multiple domains. Generally, a key challen…
Event Causality Extraction with Event Argument Correlations
Shiyao Cui, Jiawei Sheng, Xin Cong +3
Event Causality Identification (ECI), which aims to detect whether a causality relation exists between two given textual events, is an important task for event causality understand…
Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
Jiangxia Cao, Jiawei Sheng, Xin Cong +2
Recommender systems have been widely deployed in many real-world applications, but usually suffer from the long-standing user cold-start problem. As a promising way, Cross-Domain R…
Document-Level Event Extraction via Human-Like Reading Process
Shiyao Cui, Xin Cong, Bowen Yu +3
Document-level Event Extraction (DEE) is particularly tricky due to the two challenges it poses: scattering-arguments and multi-events. The first challenge means that arguments of…
Enhanced Language Representation with Label Knowledge for Span Extraction
Pan Yang, Xin Cong, Zhenyun Sun +1
Span extraction, aiming to extract text spans (such as words or phrases) from plain texts, is a fundamental process in Information Extraction. Recent works introduce the label know…
Deep Structural Point Process for Learning Temporal Interaction Networks
Jiangxia Cao, Xixun Lin, Xin Cong +4
This work investigates the problem of learning temporal interaction networks. A temporal interaction network consists of a series of chronological interactions between users and it…
Label Enhanced Event Detection with Heterogeneous Graph Attention Networks
Shiyao Cui, Bowen Yu, Xin Cong +3
Event Detection (ED) aims to recognize instances of specified types of event triggers in text. Different from English ED, Chinese ED suffers from the problem of word-trigger mismat…
Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
Xin Cong, Shiyao Cui, Bowen Yu +3
Event detection tends to struggle when it needs to recognize novel event types with a few samples. The previous work attempts to solve this problem in the identify-then-classify ma…