HPME proposes hard-perturbation mixup explainer grounded in generalized Graph Information Bottleneck to extract discrete subgraphs and generate in-distribution explanations that outperform soft-mask approaches on synthetic and real datasets.
Generative Diffusion Models on Graphs: Methods and Applications , url =
4 Pith papers cite this work. Polarity classification is still indexing.
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BlockGen enables flexible blockwise diffusion modeling with mixed block sizes and ARPC sampling, finding uniform diffusion outperforms masked under ancestral sampling in few-step regimes while the gap reverses with ARPC at high NFE.
GO-Flow applies manifold decomposition to flow matching for molecular conformations by separating translation, SO(3) rotation, and conformation spaces.
Large vision-language models applied to multi-scale remote sensing imagery can generate recommendations on built environment design, constructability, land use, and risks for smart city decision-making.
citing papers explorer
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Beyond Soft Masks: Hard-Perturbation Mixup Explainer for Robust GNN Explainability
HPME proposes hard-perturbation mixup explainer grounded in generalized Graph Information Bottleneck to extract discrete subgraphs and generate in-distribution explanations that outperform soft-mask approaches on synthetic and real datasets.
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BlockGen: Flexible Blockwise Sequence Modeling with Hybrid Samplers
BlockGen enables flexible blockwise diffusion modeling with mixed block sizes and ARPC sampling, finding uniform diffusion outperforms masked under ancestral sampling in few-step regimes while the gap reverses with ARPC at high NFE.
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Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition
GO-Flow applies manifold decomposition to flow matching for molecular conformations by separating translation, SO(3) rotation, and conformation spaces.
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Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models
Large vision-language models applied to multi-scale remote sensing imagery can generate recommendations on built environment design, constructability, land use, and risks for smart city decision-making.