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Shadow-Loom framework uses causal reasoning for narrative world models

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Shadow-Loom, an open-source framework designed to create graphical world models from narratives. This system employs causal physics based on Judea Pearl's work and a narrative physics engine to analyze reader engagement through states like mystery and suspense. While large language models are used for boundary tasks such as extraction and audit, the core reasoning processes are handled by typed code operating on the graph. AI

IMPACT Introduces a novel framework for narrative analysis that separates core reasoning from LLM boundary tasks.

RANK_REASON The cluster describes an academic paper detailing an experimental open-source framework for narrative analysis.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Shadow-Loom framework uses causal reasoning for narrative world models

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The cluster describes an academic paper detailing an experimental open-source framework for narrative analysis.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · David Wilmot ·

    Shadow-Loom: Causal Reasoning over Graphical World Model of Narratives

    arXiv:2605.02475v1 Announce Type: cross Abstract: Stories hold a reader's attention because they have causes, secrets, and consequences. Shadow-Loom is an experimental open-source framework that turns a narrative into a versioned graphical world model and lets two engines act on …

  2. arXiv cs.CL TIER_1 English(EN) · David Wilmot ·

    Shadow-Loom: Causal Reasoning over Graphical World Model of Narratives

    Stories hold a reader's attention because they have causes, secrets, and consequences. Shadow-Loom is an experimental open-source framework that turns a narrative into a versioned graphical world model and lets two engines act on it: a causal physics grounded in Pearl's ladder of…

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