32 papers
Model Forensics: Investigating Whether Concerning Behavior Reflects Misalignment
Aditya Singh, Gerson Kroiz, Senthooran Rajamanoharan +1
A central goal of safety research is determining whether a model is misaligned. Prior work has largely focused on detecting concerning behavior. But behavior alone does not establi…
How Transparent is DiffusionGemma?
Joshua Engels, Callum McDougall, Bilal Chughtai +13
LLM reasoning transparency is a critical affordance for understanding model decisions, mitigating misuse and misalignment, and debugging surprising model behaviors. However, Diffus…
Chain-of-Thought Reasoning In The Wild Is Not Always Faithful
Iván Arcuschin, Jett Janiak, Robert Krzyzanowski +3
Recent studies indicate that when faced with explicit biases in prompts, models often omit mentioning these biases in their Chain-of-Thought (CoT) output, revealing that verbalized…
How Well Do Models Follow Their Constitutions?
Arya Jakkli, Senthooran Rajamanoharan, Neel Nanda
Frontier AI developers now train models against long written behavioral specifications, such as Anthropic's constitution (Anthropic, 2025a) and OpenAI's Model Spec (OpenAI, 2025a),…
Censored LLMs as a Natural Testbed for Secret Knowledge Elicitation
Helena Casademunt, Bartosz CywiÅski, Khoi Tran +3
Large language models sometimes produce false or misleading responses. Two approaches to this problem are honesty elicitation -- modifying prompts or weights so that the model answ…
Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences
Julian Minder, Clément Dumas, Stewart Slocum +4
Finetuning on narrow domains has become an essential tool to adapt Large Language Models (LLMs) to specific tasks and to create models with known unusual properties that are useful…