Why It Hurts: Identifying the Drivers of Negative Thoughts in Emotional Support Conversations
Large Language Models (LLMs) are increasingly used for emotional support tasks, such as negative thought reframing. This task relies on modifying cognitive appraisals, the subjective interpretation of events that elicit negative emotions, which is typically conceptualized along multiple discrete dimensions. Current LLM-based frameworks model cognitive appraisal by exhaustively evaluating all possible dimensions, but they fail to account for the varying saliency of these dimensions across different contexts. In this work, we investigate a vital yet overlooked question: "Can LLMs infer the salient appraisal dimensions from emotional support conversations?" To address this question, we intro...
| Authors | Hainiu Xu, Zhaoyue Sun, Hanqi Yan et al. |
|---|---|
| Primary category | cs.HC |
| Published | 2 June 2026 |
| Last updated at source | 29 August 2026 |
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