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Fine-tuned models can outperform leading systems in automated fact-checking, but their effectiveness is highly dependent on the domain and evaluation metrics used.
Overlap-based metrics inflate reliability scores in narrative graph annotation, while locally-constrained graph representations can significantly reduce annotation variability.
