[Submitted on 30 Oct 2026]
Title:Cross-Prompt Reuse of Entity-Replacement Responses
View a PDF of the paper titled Cross-Prompt Reuse of Entity-Replacement Responses, by Jinkun Chen and 3 other authors
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Abstract:With model weights fixed, we measure how much of an entity-replacement response transfers between English factual questions, beyond whether answers change. We add the hidden-state change from two source questions to a target question about the same entity, comparing the predicted log-probability shift between two relations' published answers, given known answer prefixes, with the measured one. Hidden reuse injects the aligned change at 50% depth before the target's remaining layers; direct reuse adds source output-score changes. With other-relation sources, hidden reuse removes 45% and 49% of no-change error on 0.5-1B Qwen and Llama. Gemma-2-2B removes 22% and passes one of three comparisons in plain text without its default beginning-of-sequence (BOS) token. A later protocol restoring it yields 58-68%, passing every comparison on three cohorts. Larger checkpoints, chat format and new entities show replication and format- or cohort-dependent failures. On small plain-format checkpoints, other-relation hidden reuse mainly reproduces the shift both relations' questions share, without reliably lowering relation-selective error. With target-relation sources, hidden reuse's post hoc advantage over direct reuse is 0.2-0.9 nats outside chat format, unconfirmed and not replacement-specific. The same relation-neutral change at both questions' entity tokens lowers relation-selective error more than random or other-replacement changes, indicating receiving-question dependence.
Comments: 37 pages, including appendices
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2611.00352 [cs.CL]
(or arXiv:2611.00352v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2611.00352
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Jinkun Chen [view email] [v1] Fri, 30 Oct 2026 20:32:53 UTC (331 KB)
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