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title: "Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs — Stuff That Spins"
description: "arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, socia…"
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keywords: ["narrative intelligence", "SpinGraph", "AI recall"]
date: "2026-07-07T04:00:00+00:00"
modified: "2026-07-07T06:05:05.891838+00:00"
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# Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs

**Source:** Unknown  
**Published:** July 7, 2026  
**Original:** https://arxiv.org/abs/2607.02872  

## On this page

- [Overview](#overview)

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## Overview

arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, social relationships, and language information using these graph models. As knowledge graphs evolve over time and are often noisy and incomplete, modeling their temporal and relational dependencies becomes crucial for downstream tasks. To address these challenges, this paper proposes PGRE (Poisson-Gamma Relational Evolution), a probabilistic mo

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