5 papers · 1 filter
Semantic DLM+: Improving Diffusion Language Models through Bias-variance Trade-off in Transition Kernel Design
Keyue Jiang, Yuxiang Wang, Yanan Zhao +7
Diffusion Language Models (DLMs) have demonstrated strong scaling capacity as alternatives to autoregressive language models. However, their performance is highly sensitive to the…
Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes
Keyue Jiang, Bohan Tang, Xiaowen Dong +1
Inferring the graph structure from observed data is a key task in graph machine learning to capture the intrinsic relationship between data entities. While significant advancements…
Training-Free Message Passing for Learning on Hypergraphs
Bohan Tang, Zexi Liu, Keyue Jiang +2
Hypergraphs are crucial for modelling higher-order interactions in real-world data. Hypergraph neural networks (HNNs) effectively utilise these structures by message passing to gen…
Hypergraph-MLP: Learning on Hypergraphs without Message Passing
Bohan Tang, Siheng Chen, Xiaowen Dong
Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing. Many hypergraph…
Hypergraph Transformer for Semi-Supervised Classification
Zexi Liu, Bohan Tang, Ziyuan Ye +3
Hypergraphs play a pivotal role in the modelling of data featuring higher-order relations involving more than two entities. Hypergraph neural networks emerge as a powerful tool for…