Papers by Keigo Shibata

1 papers
Suppressing Final Layer Hidden State Jumps in Transformer Pretraining (2026.findings-eacl)

Copied to clipboard

Challenge: Existing models exhibit only slight changes in the angular distance between the input and output hidden state vectors in the middle layers .
Approach: They propose a jump-suppressing regularizer which penalizes large hidden state displacements near the final layer during pre-training.
Outcome: The proposed method significantly reduces hidden state jumps in the final layer and increases model capacity.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations