May 23, 2023 · We propose Contrastive Graph-Text pretraining (ConGraT), a general, self-supervised approach for jointly learning separate representations of texts and nodes ...
In this work, we propose Contrastive Graph-Text pretraining (ConGraT), a general, self-supervised approach for jointly learning separate representations of ...
Mar 14, 2024 · Our method uses two separate encoders for graph nodes and texts, which are trained to align their representations within a common latent space.
Jul 9, 2024 · We propose ConGraT, a general self-supervised pretraining method for jointly learning graph node and text representations on TAGs, such as citation, link, or ...
We propose ConGraT(Contrastive Graph-Text pretraining), a general, self-supervised method for jointly learning separate representations of texts and nodes.
1 day ago · We propose ConGraT(Contrastive Graph-Text pretraining), a general, self-supervised method for jointly learning separate representations of ...
Jul 10, 2024 · The paper proposes a new self-supervised approach called Contrastive Graph-Text pretraining (ConGraT) for jointly learning representations of ...
... text-attributed graph representation learning. [pdf]; [arxiv 2023.05] Congrat: Self-supervised contrastive pretraining for joint graph and text embeddings.
3. ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings · We propose a contrastive method to jointly learn graph and text ...
Article "ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings" Detailed information of the J-GLOBAL is an information ...