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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.03147 |
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| _version_ | 1866914544587112448 |
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| author | Sun, Lihao Yan, Lewen Lu, Xiaoya Lee, Andrew Zhang, Jie Shao, Jing |
| author_facet | Sun, Lihao Yan, Lewen Lu, Xiaoya Lee, Andrew Zhang, Jie Shao, Jing |
| contents | We show that emotion vectors in LLMs are organized by a two-dimensional valence-arousal (VA) subspace exhibiting circular geometry. Through principal component decomposition and ridge regression, we recover meaningful VA axes underlying emotion steering vectors whose projections correlate with human affect ratings across 44,728 words. Steering along these axes produces monotonic control over the affective properties of generated text, and further affords bidirectional control over multiple downstream behaviors (refusal and sycophancy) from a single subspace. These effects replicate across Llama-3.1-8B, Qwen3-8B, and Qwen3-14B. We propose lexical mediation to explain why these effects and prior emotionally framed controls work: refusal and compliance tokens occupy distinct VA regions, and VA steering directly modulates their emission probabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_03147 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control Sun, Lihao Yan, Lewen Lu, Xiaoya Lee, Andrew Zhang, Jie Shao, Jing Computation and Language Artificial Intelligence Computers and Society We show that emotion vectors in LLMs are organized by a two-dimensional valence-arousal (VA) subspace exhibiting circular geometry. Through principal component decomposition and ridge regression, we recover meaningful VA axes underlying emotion steering vectors whose projections correlate with human affect ratings across 44,728 words. Steering along these axes produces monotonic control over the affective properties of generated text, and further affords bidirectional control over multiple downstream behaviors (refusal and sycophancy) from a single subspace. These effects replicate across Llama-3.1-8B, Qwen3-8B, and Qwen3-14B. We propose lexical mediation to explain why these effects and prior emotionally framed controls work: refusal and compliance tokens occupy distinct VA regions, and VA steering directly modulates their emission probabilities. |
| title | Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control |
| topic | Computation and Language Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2604.03147 |