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Linearized Graph Sequence Models
Linearized Graph Sequence Models
PulseAugur coverage of Linearized Graph Sequence Models — every cluster mentioning Linearized Graph Sequence Models across labs, papers, and developer communities, ranked by signal.
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HOPPER framework enhances graph sequence models with learnable hop extraction
Researchers have introduced HOPPER, a novel framework designed to enhance Linearized Graph Sequence Models (LGSMs). Unlike previous LGSMs that rely on fixed graph operators, HOPPER enables end-to-end learning of hop seq…
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New framework recasts graph learning via sequence modeling
Researchers have introduced a new framework called Linearized Graph Sequence Models, which reframes message-passing graph computations from a sequence modeling perspective. This approach aims to simplify architectural c…