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cs.AI2026
Don't Inoculate Everything: Stratified Inoculation Prompting Narrows Backdoor Triggers and Preserves Desired Traits
Kajetan Dymkiewicz, Tim Farrelly, Adam Práda +8
Supervised fine-tuning can teach language models undesired behaviours alongside desired ones. Inoculation prompting (IP) aims to limit unwanted generalisation by requesting the und…
cs.AI2026
Inoculation Adapters: Improved Selective Generalization of Capabilities with Fewer Surprising Backdoors
Maxime Riché, Daniel Tan, Vili Kohonen +1
Inoculation prompting is a selective-generalization technique used against Emergent Misalignment. We introduce inoculation adapters (IA), a family of methods that similarly reduce…
cs.AI2026
Implementing surrogate goals for safer bargaining in LLM-based agents
Caspar Oesterheld, Maxime Riché, Filip Sondej +2
Surrogate goals have been proposed as a strategy for reducing risks from bargaining failures. A surrogate goal is goal that a principal can give an AI agent and that deflects any t…