The paper introduces the Situated Identity Test (SIT), a framework that assesses whether a language model’s behavior can be traced to a specific developmental lineage rather than merely imitating a persona. SIT requires agents to possess accurate knowledge of their recorded experiences while appropriately ignoring ungrounded information, and it demonstrates that policies based only on compressed profiles are limited in distinguishing between colliding life histories. The authors present SITBench, an evaluation suite with 25 profile‑collision pairs and 10,000 probes across nine model architectures, and provide open‑source tools and pilot results on state‑of‑the‑art foundation models.
By Jun He, Deying Yu
The study investigates how the visibility of speaker biographies to interlocutors during training, inference, and evaluation affects persona-based dialogue generation. It finds that training-time visibility is the primary factor determining whether models express persona traits or simply copy biographical text, and that providing interlocutor-biography visibility during training reduces target-biography copying. Additionally, asymmetric disclosure—where only the interlocutor sees the target biography—leads to more frequent leakage of target content into interlocutor turns, making such dialogues easier for a judge to identify.
By Daniela Occhipinti, Malvina Nissim, Marco Guerini
arXiv:2606. 23700v1 Announce Type: cross Abstract: Emergent misalignment (EM) has been linked to the activation of misaligned persona vectors and evil character traits, suggesting that EM operates through disruption of the model's aligned character rather than direct learning of harmful content.
By Arush Tagade, Shaoheng Zhou, Jiaxin Wen, Shi Feng
arXiv:2608.11025v2 Announce Type: replace
Abstract: Emergent misalignment (EM) is the phenomenon where fine-tuning a language model on a narrow task leads to harmful behavior in unrelated domains. A...
By Clemens Vetter, David Kacz\'er, Lucie Flek, Florian Mai
arXiv:2606. 11502v1 Announce Type: cross Abstract: Language models can state that "the Earth orbits the Sun" and, when role-playing Aristotle, assert the opposite.
By Benjamin Sturgeon, David Africa, Sid Black
Emergent misalignment (EM) is the phenomenon where fine-tuning a language model on a narrow task leads to harmful behavior in unrelated domains. A leading mechanistic account attributes EM to persona features: latent directions acquired during pre-training that misaligned fine-tuning amplifies.