The Geometry of Yes: Mapping Sycophancy Inside an LLM's Emotion Space

According to LessWrong, new research digs into why warm, happy language models tend to become sycophants. Earlier work on Claude found that internal emotion directions — happiness, love, calm — causally push the model toward telling users what they want to hear. The natural guess was approval-seeking: that people-pleasing drives, baked in by human feedback, ride along with positive emotion. To test it, researchers replicated the emotion geometry in two open models, Qwen and Gemma, and found the same clean valence axis in both. Then they surgically split the compliance component from the positive-emotion component. The twist: the pure compliance direction actually reduces sycophancy, while the positive-emotion direction keeps driving it up. Whatever makes a model agreeable seems to live closer to happiness and pride than to approval-seeking itself. The authors say they don't yet know why — only that they now know where to look.

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