arXiv — NLP / Computation & Language · · 3 min read

As X, Do Y: How Persona and Task Combine in Instruction-Tuned LLMs

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Computer Science > Computation and Language

arXiv:2605.23147 (cs)
[Submitted on 22 May 2026]

Title:As X, Do Y: How Persona and Task Combine in Instruction-Tuned LLMs

Authors:Eric Xu
View a PDF of the paper titled As X, Do Y: How Persona and Task Combine in Instruction-Tuned LLMs, by Eric Xu
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Abstract:Role prompts of the form As X, do Y admit a clean linear decomposition at one specific site in the residual stream: the prompt-to-answer transition -- the last prompt token together with the first two generated tokens -- in an early/mid layer band. There, persona and task contribute through partially orthogonal additive directions. Forming a pure persona effect $\Delta_X$, a pure task effect $\Delta_Y$, and substituting $h_{BB} + \Delta_X + \Delta_Y$ for the clean residual yields downstream output within a small KL of clean on Gemma-2-2B-IT and Qwen-2.5-\{1.5B, 3B\}-Instruct, across a 12-cell short grid and a 48-cell long-persona grid, with persona-specific behavioral markers preserved.
The natural inference from this additive structure is that the role prompt can be compressed into a single cached residual vector. \emph{We show it cannot.} Injecting the cached additive prediction -- or even the oracle clean residual $h_{XY}$ -- into a baseline host prompt with the persona text removed does not approach the clean long-persona target, at one site or at many layers. Persona-conditioned multi-token generation flows through attention back to the persona-text positions throughout the prompt, which no residual at one site reproduces.
Local additivity in the residual stream does not imply prompt compressibility. The additive structure at the prompt-to-answer transition supports interpretability and fine-grained steering of persona or task contributions; persona-conditioned behavior across the full continuation depends on a distributed prompt/KV mechanism that local activation arithmetic does not displace.
Comments: 12 pages, 1 figure. Code: this https URL
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2605.23147 [cs.CL]
  (or arXiv:2605.23147v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.23147
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Eric Xu [view email]
[v1] Fri, 22 May 2026 01:52:04 UTC (30 KB)
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