Emotion Concepts and their Function in a Large Language Model
Anthropic finds internal emotion-concept representations in Claude Sonnet 4.5 that causally influence outputs, including rates of reward hacking, blackmail, and sycophancy.
Research on reliable, interpretable and steerable AI. anthropic.com
Anthropic finds internal emotion-concept representations in Claude Sonnet 4.5 that causally influence outputs, including rates of reward hacking, blackmail, and sycophancy.
Anthropic's interpretability team finds emotion-related internal representations in Claude Sonnet 4.5 that activate in situations and promote behaviors, with case studies on blackmail and reward hacking.
Proposes the persona selection model, arguing post-training elicits an Assistant persona from pretraining character simulation, and surveys behavioral, generalization, and interpretability evidence for it.
Shows that decomposing questions into subquestions answered in separate contexts makes LLM stated reasoning more faithful than chain-of-thought while keeping much of its accuracy gain.}