Poster "transformers architecture" Papers

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A Formal Framework for Understanding Length Generalization in Transformers

Xinting Huang, Andy Yang, Satwik Bhattamishra et al.

ICLR 2025arXiv:2410.02140
29
citations

Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data?

Yutong Yin, Zhaoran Wang

ICLR 2025arXiv:2501.15857
2
citations

Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context

Xiang Cheng, Yuxin Chen, Suvrit Sra

ICML 2024arXiv:2312.06528
63
citations

Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot

Zixuan Wang, Stanley Wei, Daniel Hsu et al.

ICML 2024arXiv:2406.06893
21
citations