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Found 5 papers, 2 papers with code
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
Cross-domain recommendation (CDR) has been proven as a promising way to tackle the user cold-start problem, which aims to make recommendations for users in the target domain by transferring the user preference derived from the source domain.
Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck
For the first issue, a refinement-regularizer probes the information-bottleneck principle to balance the predictive evidence and noisy information, yielding expressive representations for prediction.
Event Causality Extraction with Event Argument Correlations
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 understanding.
Label Enhanced Event Detection with Heterogeneous Graph Attention Networks
A heterogeneous graph attention networks is then introduced to propagate relational message and enrich information interaction.
Beyond Word Attention: Using Segment Attention in Neural Relation Extraction
Relation extraction studies the issue of predicting semantic relations between pairs of entities in sentences.
Ranked #29 on
Relation Extraction
on TACRED
