knowledge graph embedding
PulseAugur coverage of knowledge graph embedding — every cluster mentioning knowledge graph embedding across labs, papers, and developer communities, ranked by signal.
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New framework ReaLM fuses KG embeddings with LLMs; study finds KG embedding models unstable
Researchers have developed ReaLM, a new framework that bridges the gap between knowledge graph embeddings and large language models by discretizing KG embeddings into learnable tokens. This approach allows for a more ef…
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Knowledge graph embeddings approximate probabilistic inference in SEL
Researchers have developed a method to approximate probabilistic inference in Statistical EL (SEL) by leveraging knowledge graph embeddings. This approach aims to make drawing conclusions from statistical information mo…
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New framework tackles privacy risks in knowledge graph embeddings
Researchers have developed a framework to identify and mitigate privacy risks in knowledge graph embeddings (KGEs). The study demonstrates how adversaries can infer sensitive user attributes from KGE outputs, even when …
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KrausKGE model advances knowledge graph embeddings with new mathematical framework
Researchers have introduced a new framework for knowledge graph embedding (KGE) called KrausKGE, which leverages Kraus channel structures derived from mathematical axioms. This approach provides a principled foundation …
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FixV2W uses knowledge graph embeddings to improve CVE-CWE mapping accuracy
Researchers have developed FixV2W, a novel method to enhance the accuracy of mappings between Common Vulnerabilities and Exposures (CVE) and Common Weakness Enumeration (CWE) entries. This approach utilizes knowledge gr…
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Study reveals catastrophic forgetting in knowledge graph embeddings is underestimated
Researchers have identified a significant issue in evaluating Continual Knowledge Graph Embedding (CKGE) methods, termed 'entity interference.' This phenomenon occurs when new entities introduced into a knowledge graph …