As X, Do Y: How Persona and Task Combine in Instruction-Tuned LLMs
The paper discusses how persona and task can be combined in instruction-tuned language models. It highlights the limitations of compressing role prompts into a single cached residual vector. The findings suggest that local additivity in the residual stream does not imply prompt compressibility.
- ▪Role prompts of the form As X, do Y allow for a linear decomposition at the prompt-to-answer transition.
- ▪The study shows that persona-conditioned behavior relies on a distributed prompt/KV mechanism.
- ▪Injecting cached predictions into a baseline prompt does not yield the desired clean long-persona target.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.23147 |
| Publication time | Mon, 25 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-25T04:07:35.648Z |
| Last seen | 2026-05-25T04:07:35.648Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | HqLYeM-uis7k · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
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| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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 View PDF HTML (experimental) 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.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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