Kenneth Zhang

1paper

1 Paper

CLJan 1
BERT-JEPA: Reorganizing CLS Embeddings for Language-Invariant Semantics

Taj Gillin, Adam Lalani, Kenneth Zhang et al.

Joint Embedding Predictive Architectures (JEPA) are a novel self supervised training technique that have shown recent promise across domains. We introduce BERT-JEPA (BEPA), a training paradigm that adds a JEPA training objective to BERT-style models, working to combat a collapsed [CLS] embedding space and turning it into a language-agnostic space. This new structure leads to increased performance across multilingual benchmarks.