Yearly Archives: 2024

Happy to share our latest paper titled “Sememe Based Semantic Communications” published in IEEE Communications Letters! We introduced a concept in linguistics called sememes to the domain of semantic communications. Sememes are the smallest and indivisible semantic units of word meaning. A predefined set of sememes is theoretically considered “the periodic table” of meaning in […]

We are happy to announce that we demonstrated our latest work titled “VISPool: Enhancing Transformer Encoders with Vector Visibility Graph Neural Networks” at ACL 2024, Bangkok/Thailand!   In our #ACL2024 paper, we explore the powerful combination of transformers and graph neural networks (GNNs) to push the boundaries of natural language processing (NLP). While transformers have […]

We are pleased to announce that our paper on generalizing the fractional Fourier transform to the graph domain titled “Graph Fractional Fourier Transform: A Unified Theory” published in IEEE Transactions on Signal Processing! Highlights of our contributions include: A rigorous extension of the fractional power-based definition of GFRFT to support any graph structure and transform […]

Happy to share our latest paper titled “Text-RGNNs: Relational Modeling for Heterogeneous Text Graphs” published in IEEE Signal Processing Letters! Building on the foundational Text-graph convolutional Network (TextGCN), which represents corpus with heterogeneous text graphs, we addressed a key limitation: GCNs are inherently designed to operate within homogeneous graphs, potentially limiting their performance. To overcome […]