Locating and Controlling Implicit Personalization in Large Language Models
Large language models (LLMs) often shift their outputs in response to implicit demographic cues even when users never state a demographic identity. Previous work has documented this behavior, but the connection between these behavioral changes and the model's internal activations remains unclear. Using matched cued and neutral conversations across five LLMs, we establish that a localized internal activation signal tracks changes in recommendations, with correlations up to r=0.87. When multiple cues appear together, their internal signals largely combine, but the changes in output do not simply add up. We further show that removing the internal signal associated with one cue can suppress i...
| Authors | Yueru Yan, Siqi Wu, Thai Le |
|---|---|
| Primary category | cs.CL |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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