KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation

Ta-Chung Chi, Ting-Han Fan, Peter J. Ramadge, Alexander Rudnicky. KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation. In Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, A. Oh, editors, Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022. 2022. [doi]

@inproceedings{ChiFRR22,
  title = {KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation},
  author = {Ta-Chung Chi and Ting-Han Fan and Peter J. Ramadge and Alexander Rudnicky},
  year = {2022},
  url = {http://papers.nips.cc/paper_files/paper/2022/hash/37a413841a614b5414b333585e7613b8-Abstract-Conference.html},
  researchr = {https://researchr.org/publication/ChiFRR22},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022},
  editor = {Sanmi Koyejo and S. Mohamed and A. Agarwal and Danielle Belgrave and K. Cho and A. Oh},
  isbn = {9781713871088},
}