2021年9月1日 · Our research goal in this paper is to develop a fact verification model which can leverage multi-granularity semantic units and capture their relations for evidence …

2023年1月13日 · Easy-to-Use: OpenHGNN provides easy-to-use interfaces for running experiments with the given models and dataset. Besides, we also integrate optuna to get …

2021年9月1日 · HHGN combines multiple features of entity, sentence as well as context for evidence representation, and employs a heterogeneous graph to capture their semantic …

2021年9月1日 · HHGN combines multiple features of entity, sentence as well as context for evidence representation, and employs a heterogeneous graph to capture their semantic …

Paper: Hierarchical Heterogeneous Graph Network based Multimodal Emotion Recognition in Conversation. If you want to download the MELD database, you can access the link: …

2021年12月30日 · To facilitate robust and reproducible HGNN research, we construct the Heterogeneous Graph Benchmark (HGB), consisting of 11 diverse datasets with three tasks. …

2019年11月9日 · By weaving heterogeneous nodes into an integral unified graph, this hierarchical differentiation of node granularity enables HGN to support different question answering sub …

A heterogeneous graph is constructed that models the participant’s depression state and uses the graph attention network to aggregate the pieces of depressive clues and uses the focal loss as …

2024年9月16日 · 基于层次推理的异构图神经网络（HHGN）是一种用于事实验证的深度学习模型。 这种模型通过结合多个特征和层次推理策略，增强了对复杂证据的表示和处理能力。 …

2021年9月1日 · HHGN combines multiple features of entity, sentence as well as context for evidence representation, and employs a heterogeneous graph to capture their semantic …