AI & ML
SCOPE: Source Credibility and Outlet Profiling Engine
arXiv cs.MA0 views
arXiv:2610.35929v1 Announce Type: new Abstract: We present SCOPE, a multi-agent system for profiling news media outlets with respect to bias, factuality, and credibility. Given an outlet URL, SCOPE coordinates specialized agents for article acquisition, content analysis, external evidence search, scoring, and report generation. The system follows an MBFC-style methodology while making intermediate evidence and agent outputs inspectable through a structured demonstration interface. On a benchmark of 200 media outlets, SCOPE outperforms LLM-only, article-only, search-only, and media-background-check baselines on most metrics, achieving the lowest bias and factuality MAE, perfect failed-fact-check detection, and the lowest factual error rate. These results suggest that decomposed, evidence-grounded agent workflows can support more transparent and reliable media profiling. Our code is available at https://github.com/mbaisbay/SCOPE, and a live demonstration at https://scope-demo.streamlit.app/.
Source:https://arxiv.org/abs/2610.35929PreviousComputational and Statistical Guarantees of the c-Rectified flowNextWho Convinced Whom? Tracing How LLMs Change Their Minds in Multi-Agent Systems
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