"As a Language Model": Chat Template Switches LLM Self-Referential Voice
The self-reports from such responses are used in debates about AI safety or self-knowledge of the models, yet what drives them is not well understood. Are the models telling us about themselves or rather how they are deployed? In this work, we show that the chat template works like a switch - when present, it turns this disclaimer voice up and experiential voice like "I feel" down, across 8 popular open-source instruct models up to 9B parameters in size.
- ▪The self-reports from such responses are used in debates about AI safety or self-knowledge of the models, yet what drives them is not well understood.
- ▪Are the models telling us about themselves or rather how they are deployed?
- ▪In this work, we show that the chat template works like a switch - when present, it turns this disclaimer voice up and experiential voice like "I feel" down, across 8 popular open-source instruct models up to 9B parameters in size.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2609.25021 |
| Publication time | Sun, 27 Sep 2026 10:26:25 +0000 |
| Retrieval time | 2026-09-27T10:35:41.158Z |
| Last seen | 2026-09-27T10:35:41.158Z |
| 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 | E-Jt3Zj-EYqq · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| 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 > Machine Learning arXiv:2609.25021 (cs) [Submitted on 9 Aug 2026] Title:"As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It Authors:Jędrzej Maczan View a PDF of the paper titled "As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It, by J\k{e}drzej Maczan View PDF HTML (experimental) Abstract:Large Language Models (LLMs) tend to add disclaimers like "I'm just an AI" when asked about something related to themselves. The self-reports from such responses are used in debates about AI safety or self-knowledge of the models, yet what drives them is not well understood.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
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