paper-conference

CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning

Continual self-supervised learning (CSSL) learns a series of tasks sequentially on the unlabeled data. Two main challenges of con- …

Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, J Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning

Do LLMs Recognize me, When I is not me: Assessment of LLMs Understanding of Turkish Indexical Pronouns in Indexical Shift Contexts

In this work, we introduce the Learnable Response Scoring Function (LARS) for Uncertainty Estimation (UE) in generative Large Language …

Metehan Oguz, Y. Umut Ciftci, Yavuz Faruk Bakman

MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs

Generative Large Language Models (LLMs) are widely utilized for their excellence in vari- ous tasks. However, their tendency to produce …

Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning

Current literature in FL mostly focuses on single-task learning. However, over time, new tasks may appear in the clients and the global …

Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr

Federated Alternate Training (FAT): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging

Federated Learning (FL) aims to train a machine learning (ML) model in a distributed fashion to strengthen data privacy with limited …

Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr

Federated Alternate Training (FAT): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging