TEMPER: Testing Emotional Perturbation in Quantitative Reasoning
Large language models are trained and evaluated on quantitative reasoning tasks written in clean, emotionally neutral language. However, real-world queries are often wrapped in frustration, urgency or enthusiasm. Does emotional framing alone degrade reasoning when all numerical content is preserved? To investigate this, a controlled emotion translation framework is developed that rewrites problems into emotional variants while preserving all quantities and relationships. Using this framework, Temper-5400 (5,400 semantically verified emotion-neutral pairs) is constructed across GSM8K, MultiArith, and ARC-Challenge, and evaluated on eighteen models (1B to frontier scale). Two core results e...
| Authors | Atahan Dokme, Benjamin Reichman, Larry Heck |
|---|---|
| Primary category | cs.CL |
| Published | 9 April 2026 |
| Last updated at source | 12 August 2026 |
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