{"paper":{"title":"The Limits of LLM Forecasting: Parametric Knowledge Gaps Across Conflict Zones","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Poli Nemkova","submitted_at":"2026-05-29T19:00:48Z","abstract_excerpt":"Media coverage of armed conflict is deeply asymmetric: we document a 224$\\times$ gap between the most and least covered conflict zones in English-language media across 22 countries (2020--2026). We evaluate zero-shot conflict escalation forecasting across all 22 countries on a 660-case held-out test set, comparing Llama-3.3-70B and GPT-4o against three structured baselines.\n  The central finding is not a performance gradient but a qualitative failure: LLMs do not forecast conflict -- they categorize it. Llama predicts escalation on every under-covered case, matching the trivial Always-YES base"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00018","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.00018/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}