Names That Steer: Identifier Bias Across Text and Vision in Code Understanding

Code is increasingly presented to multimodal models as rendered images, yet little is known about whether visual presentation changes how symbolic cues shape program understanding. We trace identifier bias across textual and visual code using a semantics-preserving source–donor construction that holds a source implementation fixed while replacing its identifiers with names from a functionally different donor. Across eight vision-capable model instances, donor-aligned names shift both functional choices and open-ended summaries toward the donor under Text and Readable Image. The Readable Image choice effect is positive in every instance (4.2–22.8 percentage points) and exceeds its Text counterpart in all eight, although carrier differences vary by task and readout. Readback and constrained visual controls make gross transcription failure insufficient to explain this persistence. In an open-weight focal model, we further examine carrier-conditioned output likelihood, cross-carrier representation geometry, and activation patching. Text and Image yield strongly corresponding representations, and identifier-induced changes align more closely for the same program than across programs. A matched Text direction steers Image judgments more than a mismatched direction, while a same-carrier Image direction remains stronger. Similar generated summaries nevertheless retain a self-carrier likelihood advantage. Together, these findings are consistent with a partial-anchoring account in which visual-code representations share text-compatible, program-specific components while retaining carrier-conditioned structure. Identifier bias therefore persists beyond textual input, and text-derived identifier directions can functionally steer image judgments.