WebSep 7, 2024 · To sum up, we propose a novel multi-task learning model using GCN , BERT and Transformer , named GBERT, short for Graph enhanced BERT. Our contributions are summarized as follows: We employ BERT in the low-level layers of our model to get better content features. And we explicitly model the interactions between stance and rumor task. WebApr 14, 2024 · A motivation example of our knowledge graph completion model on sparse entities. Considering a sparse entity , the semantics of this entity is difficult to be modeled by traditional methods due to the data scarcity.While in our method, the entity is split into multiple fine-grained components (such as and ).Thus the semantics of these fine …
fine-tuning BERT in different tasks (Devlin et al., 2024)
WebApr 10, 2024 · In this paper, we propose an Enhanced Multi-Channel Graph Convolutional Network model (EMC-GCN) to fully utilize the relations between words. Specifically, we first define ten types of relations for ASTE task, and then adopt a biaffine attention module to embed these relations as an adjacent tensor between words in a sentence. WebGraph Enhanced BERT for Query Understanding Query understanding plays a key role in exploring users' search intents ... 0 Juanhui Li, et al. ∙. share ... poppy playtime fan games
BERT-QE: Contextualized Query Expansion for Document Re …
WebGraph Enhanced BERT for Query Understanding Conference acronym ’XX, June 03–05, 2024, Woodstock, NY query graph is built from the query-url bipartite graph [12], where … WebApr 3, 2024 · In particular, to incorporate search logs into pre-training, we first construct a query graph where nodes are queries and two queries are connected if they lead to clicks on the same urls. Then we propose a novel graph-enhanced pre-training framework, GE-BERT, which can leverage both query content and the query graph. Webpredicting the event links using a graph-enhanced BERT model (GraphBERT). As shown in Fig-ure 1 (b), we collect event structure information into a BERT model with graph structure extension. Given a set of event contexts, we use the Graph-BERT model to construct an event graph structure by predicting connection strengths between context sharing galicia