arXiv:2606. 14668v1 Announce Type: new Abstract: Knowledge editing systems must update selected facts while preserving nearby but irrelevant behavior.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.
The paper reports that existing knowledge‑editing benchmarks cannot evaluate the scope decision—whether a stored edit applies to a query—because they are counterfactual and lack negative examples. Using the gradient‑free editor INLAY, the authors exhaustively test every router action on 1,689 queries across three datasets and find that an oracle router achieves no gain over a static policy, and abstention never wins. The authors attribute this to the structural design of the benchmarks and demonstrate that adding a missing negative condition restores some headroom and allows abstention to win.
Every memory-based knowledge editor in the SERAC lineage depends on a scope decision: given a query, does a stored edit apply? We report that current knowledge-editing benchmarks cannot measure this d...
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