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Unveiling Key Aspects of Fine-Tuning in Sentence Embeddings: A
  Representation Rank Analysis

Unveiling Key Aspects of Fine-Tuning in Sentence Embeddings: A Representation Rank Analysis

18 May 2024
Euna Jung
Jaeill Kim
Jungmin Ko
Jinwoo Park
Wonjong Rhee
ArXivPDFHTML

Papers citing "Unveiling Key Aspects of Fine-Tuning in Sentence Embeddings: A Representation Rank Analysis"

4 / 4 papers shown
Title
RankMe: Assessing the downstream performance of pretrained
  self-supervised representations by their rank
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank
Q. Garrido
Randall Balestriero
Laurent Najman
Yann LeCun
SSL
39
71
0
05 Oct 2022
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of
  Unsupervised Sentence Embedding
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence Embedding
Xing Wu
Chaochen Gao
Liangjun Zang
Jizhong Han
Zhongyuan Wang
Songlin Hu
SSL
AILaw
23
127
0
09 Sep 2021
On Feature Decorrelation in Self-Supervised Learning
On Feature Decorrelation in Self-Supervised Learning
Tianyu Hua
Wenxiao Wang
Zihui Xue
Sucheng Ren
Yue Wang
Hang Zhao
SSL
OOD
107
163
0
02 May 2021
What you can cram into a single vector: Probing sentence embeddings for
  linguistic properties
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
Germán Kruszewski
Guillaume Lample
Loïc Barrault
Marco Baroni
199
876
0
03 May 2018
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