25 citations · 33 across the 12 of their papers we have counts for
5 papers · 1 filter
Beyond Owls: Subliminal Learning Can Transfer Learned Capabilities and Backdoors
Jan Dubiński, Anna Sztyber-Betley, Jan Betley +1
In subliminal learning (SL), a teacher model passes on a trait to a student model by distillation on data semantically unrelated to the trait. So far, SL has been demonstrated for…
Story Imprinting: AI Assistants Absorb Traits from Human Characters They Resemble
Jorio Cocola, Lev McKinney, Harry Mayne +2
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…
Value Leakage: An LLM's Answers Are Silently Shaped by Its Own Values
Jan Betley, Johannes Treutlein, Jan Dubiński +5
People use language models for practical questions whose answers are difficult to verify. We show that models exhibit covert value leakage: the information they provide is influenc…
Conditional misalignment: common interventions can hide emergent misalignment behind contextual triggers
Jan Dubiński, Jan Betley, Anna Sztyber-Betley +2
Finetuning a language model can lead to emergent misalignment (EM) [Betley et al., 2025b]. Models trained on a narrow distribution of misaligned behavior generalize to more egregio…
The Consciousness Cluster: Emergent preferences of Models that Claim to be Conscious
James Chua, Jan Betley, Samuel Marks +1
There is debate about whether LLMs can be conscious. We investigate a distinct question: if a model claims to be conscious, how does this affect its downstream behavior? This quest…