State of the art and potentialities of graph-level learning
Graphs have a superior ability to represent relational data, such as chemical compounds,
proteins, and social networks. Hence, graph-level learning, which takes a set of graphs as …
proteins, and social networks. Hence, graph-level learning, which takes a set of graphs as …
Community Detection in Large-Scale Complex Networks via Structural Entropy Game
Community detection is a critical task in graph theory, social network analysis, and
bioinformatics, where communities are defined as clusters of densely interconnected nodes …
bioinformatics, where communities are defined as clusters of densely interconnected nodes …
SECodec: Structural Entropy-based Compressive Speech Representation Codec for Speech Language Models
L Wang, Y Liu, Z Yu, S Gao, C Mao, Y Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
With the rapid advancement of large language models (LLMs), discrete speech
representations have become crucial for integrating speech into LLMs. Existing methods for …
representations have become crucial for integrating speech into LLMs. Existing methods for …