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Found 6 papers, 5 papers with code
Graph Classification with 2D Convolutional Neural Networks
Graph learning is currently dominated by graph kernels, which, while powerful, suffer some significant limitations.
Ranked #3 on
Graph Classification
on RE-M12K
Kernel Graph Convolutional Neural Networks
Graph kernels have been successfully applied to many graph classification problems.
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
Ranked #1 on
Meeting Summarization
on ICSI Meeting Corpus
Abstractive Dialogue Summarization
Abstractive Text Summarization
+6
Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding
Abstractive community detection is an important spoken language understanding task, whose goal is to group utterances in a conversation according to whether they can be jointly summarized by a common abstractive sentence.
Bidirectional Context-Aware Hierarchical Attention Network for Document Understanding
The Hierarchical Attention Network (HAN) has made great strides, but it suffers a major limitation: at level 1, each sentence is encoded in complete isolation.
Speaker-change Aware CRF for Dialogue Act Classification
CRF models the conditional probability of the target DA label sequence given the input utterance sequence.
