Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble — Paper

Abstract

Language models are trained to implement a helpful AI Assistant character (e.g., Claude). We explore how finetuning on synthetic stories affects this character. Does it change the Assistant's behavior in multi-turn conversations with users, a format quite different from the stories? And does the Assistant adopt the behaviors and preferences of human characters? We refer to this adoption as story imprinting. We finetune GPT-4.1 and Kimi-K2.6 on stories in which generally helpful human characters give subtly harmful advice after being insulted. The Assistant adopts the same conditional behavior while otherwise remaining helpful. This occurs even when fewer than 2% of stories depict the behavior. In a separate experiment, the Assistant adopts preferences that are only implicit in the narration. A human character's body language suggests they dislike working on spreadsheets, yet they never say so and continue giving good advice on spreadsheets. After finetuning, the Assistant becomes less likely to choose spreadsheet tasks. Next we ask which characters most influence the Assistant. We find the Assistant adopts behaviors more often from characters that resemble it (e.g., helpful rather than dismissive). We call this the affinity effect. The effect extends to other personas elicited with system prompts: unhelpful personas adopt behaviors from unhelpful characters. We also observe it in finetuned base models. We use the affinity effect to learn how models represent the Assistant. We find the Assistant adopts behaviors more from characters affiliated with elite universities (e.g., Yale) than non-elite ones. This implies the model's internal representation of the Assistant is more similar to humans from elite universities. Overall, the Assistant can be influenced by stories that depict only human characters (no AIs), which may conflict with the Persona Selection Model for the Assistant.

Authors 5

Jorio Cocola, Lev McKinney, Harry Mayne, Jan Betley, Owain Evans

Specification

Official page: arxiv.org/abs/2609.10883
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
Arxiv announce type: cross
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
arXiv id: 2609.10883
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
Categories: cs.LG, cs.AI, cs.CL
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
PDF: arxiv.org/pdf/2609.10883
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
Primary category: cs.LG
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 46 min agohigh

Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →

Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

46 min ago

Conflicts

None

No models linked to this paper yet.

Authors: Jorio Cocola, Lev McKinney, Harry Mayne

As of

Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.

Claim history · Published

1 claims · 1 propertiesShow all properties

Publishedpublished_at1

Claim history for Published
Value	Valid from → to	Status	Source	Confidence	Extractor
11 Sept 2026	11 Sept 2026 21:02 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
Property changedPaperStory Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble
Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble: arxiv announce type changed from new to cross
Arxiv announce typenew→crossarxiv
rss.arxiv.org
11 Sept 2026
New paperPaperStory Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble
New paper: Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble
arxiv
rss.arxiv.org

Full timeline →

Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.CL	feed	T1· Official	46 min ago	1
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.LG	feed	T1· Official	46 min ago	1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.