Can Emotional Profiles Help Language Models Predict Value-Aligned Actions in Value Conflict Scenarios?

Abstract

Recent work shows that language models (LMs) often claim to endorse a value but select actions inconsistent with it, a discrepancy termed the value–action gap. This gap reflects a deeper limitation: although values are fundamental to human decision-making, LMs tend to treat them as static labels rather than as dynamic priorities shaped by psychological context. In human psychology, emotion is among the most direct drivers of value prioritisation, yet no prior work has systematically tested whether conditioning an LM on an emotional profile changes how it resolves value conflicts.

Because no existing dataset is designed to test how emotion affects value-conflict resolution, we construct 616 value-conflict scenarios pairing Shalom H. Schwartz’s 56 basic values with 11 social contexts, each with six intensity-graded actions. We evaluate three LMs under six emotion conditions based on Plutchik's Wheel of Emotions and a matched neutral baseline, measuring how each emotion shifts both the model’s stated values and the actions it selects.

Emotional conditioning increases alignment in two of three models, but the effect is model-specific, where the same emotion that helps one model can worsen another and operates through different channels, shifting actions in some models and stated values in others. These findings show that emotional context can shift value–action alignment in both directions, and that its effect depends on the specific model.