NDT: Non-Differential Transformer and Its Application to Sentiment Analysis
From customer feedback to social media, understanding human sentiment in text is central to how machines can interact meaningfully with people. However, despite notable progress, accurately capturing sentiment remains a challenging task, which continues to motivate further research in this area. To this end, we introduce Non-Differential Transformer (NDT). It is inspired by (but in contrast to) the state-of-the-art Differential Transformer (DT) model. While standard Transformers can struggle with irrelevant context, the sota DT model uses attention map subtraction, potentially for noise cancellation. We explore an alternative motivation, hypothesizing that benefits may arise from enabling...
| Authors | Soudeep Ghoshal, Himanshu Buckchash, Sarita Paudel et al. |
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| Primary category | cs.IR |
| Published | 21 March 2026 |
| Last updated at source | 21 March 2026 |
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