IIET: Efficient Numerical Transformer via Implicit Iterative Euler Method (2025.emnlp-main)
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Xinyu Liu, Bei Li, Jiahao Liu, Junhao Ruan, Kechen Jiao, Hongyin Tang, Jingang Wang, Tong Xiao, JingBo Zhu
| Challenge: | High-order numerical methods enhance performance in tasks like NLP but introduce a performance-efficiency trade-off due to increased computational overhead. |
| Approach: | They propose an iterative implicit Euler Transformer which simplifies high-order numerical methods by iterating implicit Eule. |
| Outcome: | The proposed method improves accuracy and reduces inference overhead by 55% while retaining 99.4% of the original task accuracy. |
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