arXiv cs.CL· Ali Hassan Khan, Saad Bin Ather, Muhammad Saif, Maryam Bashir, Hajra Waheed·· 10 小时前AI 评分24
语言模型能感知情绪吗？Qwen2.5 情绪向量研究
Do Language Models Feel the Sentiment? Investigating Emotion Vectors
AI 导读
研究在 Qwen2.5-0.5B-Instruct 和 Qwen2.5-3B-Instruct 上考察从 GoEmotions 提取的八个情绪方向，纯情绪探针在二元 TweetEval 上分别达到 88.66% 和 90.70% 准确率。
正文 · 原文
Abstract:Emotion vectors are directions in a language model's internal representations that are associated with emotional concepts. Prior work shows that these vectors can influence model behavior, but their role in sentiment classification remains unclear. This study investigates emotion directions in Qwen2.5-0.5B-Instruct and Qwen2.5-3B-Instruct. Eight directions extracted from GoEmotions are evaluated through sentiment probing, activation interventions, and supervised correction. Emotion-only probes achieve 88.66% and 90.70% accuracy on binary TweetEval. In exploratory matched-ablation experiments, raw emotion-space removal causes 2.39 and 1.10 percentage points more accuracy loss than matched isotropic random-subspace removal for 0.5B and 3B, respectively. All four TweetEval raw and denoised effects are significant after Holm adjustment across eight comparisons. An exploratory SST-2 extension shows smaller raw excess losses of 0.66 and 0.57 points, with no effects surviving Holm adjustment. Frozen sentiment-correction classifiers are also tested on 20,000 Amazon Polarity reviews. Emotion-based correction improves accuracy over uncorrected Qwen, but does not consistently outperform margin-only baselines. These results distinguish sentiment information available in model representations, the effects of changing those representations, and their practical value for classification. They do not establish a uniquely emotional mechanism.
| Comments: | 16 pages, 3 figures, 11 tables. Accepted at ExplAI-2026: 2nd Workshop on Advanced AI in Explainability and Ethics for the Sustainable Development Goals |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2611.13744 [cs.CL] |
| (or arXiv:2611.13744v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2611.13744 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Saad Bin Ather [view email]
[v1]
Tue, 10 Nov 2026 08:45:50 UTC (793 KB)
来源：arXiv cs.CL · arxiv.org