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How Robust Are Automated Fact-Checking Systems? A Cross-Benchmark Evaluation

arXiv · AI, language, vision and robotics · article · Aug 26, 2026 · UTC

Automated fact-checking (AFC) systems retrieve evidence and predict claim veracity, yet evaluations omit simple baselines, systems are developed for a single benchmark and cannot be trusted to generalise across domains. No prior work cross-evaluates the full two-stage retrieve-then-verify pipeline across diverse datasets, complementing retrieval-only studies (Thakur et al., 2021) and single-stage benchmarking studies (Calamai et al., 2025). We benchmark nine models, ranging from random and sparse baselines to fine-tuned transformers, zero-shot LLMs, and the two highest-ranked systems from the

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Evidence & attribution

First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.