When evaluating LLM graph reconstruction, a single distance metric masks whether errors come from adding edges, removing edges, or both—the paper provides a mathematical framework to detect mixed editing and reveals different models have fundamentally different failure modes.
This paper analyzes how language models reconstruct graphs, proving mathematical bounds on the Wasserstein distance between original and reconstructed graph spectra. The bounds reveal whether a model only adds edges, only removes them, or does both—information hidden by standard distance metrics.