4 papers
SigCLR: Sigmoid Contrastive Learning of Visual Representations
Ömer Veysel Çağatan
We propose SigCLR: Sigmoid Contrastive Learning of Visual Representations. SigCLR utilizes the logistic loss that only operates on pairs and does not require a global view as in th…
UNSEE: Unsupervised Non-contrastive Sentence Embeddings
Ömer Veysel Çağatan
We present UNSEE: Unsupervised Non-Contrastive Sentence Embeddings, a novel approach that outperforms SimCSE in the Massive Text Embedding benchmark. Our exploration begins by addr…
ToddlerBERTa: Exploiting BabyBERTa for Grammar Learning and Language Understanding
Omer Veysel Cagatan
We present ToddlerBERTa, a BabyBERTa-like language model, exploring its capabilities through five different models with varied hyperparameters. Evaluating on BLiMP, SuperGLUE, MSGS…
BarlowRL: Barlow Twins for Data-Efficient Reinforcement Learning
Omer Veysel Cagatan, Baris Akgun
This paper introduces BarlowRL, a data-efficient reinforcement learning agent that combines the Barlow Twins self-supervised learning framework with DER (Data-Efficient Rainbow) al…