新闻
Disentangling Representation Evolution in Transformers through Directional Decomposition
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers decomposed transformer representation updates into parallel and perpendicular components to understand how internal representations evolve during computation.
- 为何重要
- Matters for engineers optimizing transformers, compressing models, or editing internal representations to improve performance or interpretability.
- 注意
- Study focuses on geometric analysis of existing models; unclear how findings transfer to different architectures, scales, or training regimes beyond tested cases.
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