B-cos GNNs replace non-linear message and update functions with B-cos transforms in GNNs to enable exact per-node per-feature explanations from a single forward-backward pass while retaining competitive accuracy.
arXiv preprint arXiv:2010.05563 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
SAGE is a self-evolving agentic graph-memory engine that dynamically constructs and refines structured memory graphs via writer-reader feedback, yielding performance gains on multi-hop QA, open-domain retrieval, and long-term agent benchmarks.
citing papers explorer
-
B-cos GNNs: Faithful Explanations through Dynamic Linearity
B-cos GNNs replace non-linear message and update functions with B-cos transforms in GNNs to enable exact per-node per-feature explanations from a single forward-backward pass while retaining competitive accuracy.
-
SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
SAGE is a self-evolving agentic graph-memory engine that dynamically constructs and refines structured memory graphs via writer-reader feedback, yielding performance gains on multi-hop QA, open-domain retrieval, and long-term agent benchmarks.