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What Drives LLM Self-Reflection? A Controlled Ablation of Uncertainty Routing in Armed Conflict Forecasting
Not provided in the content
reasoningaction routingLLMforecasting
2608.12322
Builder Relevance
Aug 1480%
Abstract
This study investigates the components of LLM self-reflection and identifies typed action routing as the key mechanism for improving reasoning in conflict forecasting.
Reality Card
Core Claim
Typed action routing significantly enhances LLM performance in conflict forecasting, while diagnostic scaffolding and taxonomy vocabulary do not provide measurable benefits.
Method / Result
Action routing provides a significant gain of +0.101 in F1 score over the single-shot baseline.
Limitations
The study's findings may not generalize across all conflict typologies without larger-scale evaluation.
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