The Self-Correction Illusion: LLMs Correct Others but Not Themselves

arXiv:2606.05976v1 Announce Type: cross Abstract: Recent work shows that LLM agents struggle to correct errors in their own reasoning traces yet show markedly higher correction rates when identical claims appear under external sources. We ask whether this asymmetry reflects a capability deficit or a role-label artifact: does an agent's willingness to correct a wrong claim depend causally on the chat-template role that carries it, rather than on the claim's content? Our setup keeps the erroneous claim byte-identical across all conditions (SHA-256 verified) and varies only its wrapping role: the agent's own role{}, a role{user} message, a role{tool} response, or a role{system } block. Across 13 model-domain cells covering seven model families and three domains (n{=}30 paired tasks per cell), relabeling the claim from role{} to an external role lifts the explicit-correction rate by 23 to 93 percentage points, with 10 of 13 cells reaching $p{} dominates on math, while a plain role{user} message dominates on logical deduction.

Source: arXiv cs.CL | 2026-06-05