Zobrazeno 1 - 10
of 63 524
pro vyhledávání: '"Faruk, A"'
In this paper, we address the problem of lossy semantic communication to reduce uncertainty about the State of the World (SotW) for deductive tasks in point to point communication. A key challenge is transmitting the maximum semantic information with
Externí odkaz:
http://arxiv.org/abs/2410.01676
In deep learning, transfer learning and ensemble models have shown promise in improving computer-aided disease diagnosis. However, applying the transfer learning and ensemble model is still relatively limited. Moreover, the ensemble model's developme
Externí odkaz:
http://arxiv.org/abs/2409.06699
We investigate magnetotransport across an interface between two Weyl semimetals (finite in both directions) whose Weyl nodes project onto two different surfaces which are twisted with respect to each other before being coupled. This gives rise to a n
Externí odkaz:
http://arxiv.org/abs/2408.10586
Autor:
Mushtaq, Erum, Yaldiz, Duygu Nur, Bakman, Yavuz Faruk, Ding, Jie, Tao, Chenyang, Dimitriadis, Dimitrios, Avestimehr, Salman
Continual self-supervised learning (CSSL) learns a series of tasks sequentially on the unlabeled data. Two main challenges of continual learning are catastrophic forgetting and task confusion. While CSSL problem has been studied to address the catast
Externí odkaz:
http://arxiv.org/abs/2407.12188
The advent of the sixth generation (6G) wireless networks heralds a transformative era for mobile communication, where the integration of cutting-edge technologies like Reconfigurable Intelligent Surfaces (RISs) is paramount in addressing the burgeon
Externí odkaz:
http://arxiv.org/abs/2407.04731
Autor:
Ahmed, Faruk, Sellergren, Andrew, Yang, Lin, Xu, Shawn, Babenko, Boris, Ward, Abbi, Olson, Niels, Mohtashamian, Arash, Matias, Yossi, Corrado, Greg S., Duong, Quang, Webster, Dale R., Shetty, Shravya, Golden, Daniel, Liu, Yun, Steiner, David F., Wulczyn, Ellery
Microscopic interpretation of histopathology images underlies many important diagnostic and treatment decisions. While advances in vision-language modeling raise new opportunities for analysis of such images, the gigapixel-scale size of whole slide i
Externí odkaz:
http://arxiv.org/abs/2406.19578
Recent advances in large language models (LLMs) have led to new summarization strategies, offering an extensive toolkit for extracting important information. However, these approaches are frequently limited by their reliance on isolated sources of da
Externí odkaz:
http://arxiv.org/abs/2406.13715
Autor:
Yaldiz, Duygu Nur, Bakman, Yavuz Faruk, Buyukates, Baturalp, Tao, Chenyang, Ramakrishna, Anil, Dimitriadis, Dimitrios, Avestimehr, Salman
In this work, we introduce the Learnable Response Scoring Function (LARS) for Uncertainty Estimation (UE) in generative Large Language Models (LLMs). Current scoring functions for probability-based UE, such as length-normalized scoring and semantic c
Externí odkaz:
http://arxiv.org/abs/2406.11278
Large language models (LLMs) have shown impressive capabilities in tasks such as machine translation, text summarization, question answering, and solving complex mathematical problems. However, their primary training on data-rich languages like Engli
Externí odkaz:
http://arxiv.org/abs/2406.05569
Autor:
Yang, Lin, Xu, Shawn, Sellergren, Andrew, Kohlberger, Timo, Zhou, Yuchen, Ktena, Ira, Kiraly, Atilla, Ahmed, Faruk, Hormozdiari, Farhad, Jaroensri, Tiam, Wang, Eric, Wulczyn, Ellery, Jamil, Fayaz, Guidroz, Theo, Lau, Chuck, Qiao, Siyuan, Liu, Yun, Goel, Akshay, Park, Kendall, Agharwal, Arnav, George, Nick, Wang, Yang, Tanno, Ryutaro, Barrett, David G. T., Weng, Wei-Hung, Mahdavi, S. Sara, Saab, Khaled, Tu, Tao, Kalidindi, Sreenivasa Raju, Etemadi, Mozziyar, Cuadros, Jorge, Sorensen, Gregory, Matias, Yossi, Chou, Katherine, Corrado, Greg, Barral, Joelle, Shetty, Shravya, Fleet, David, Eslami, S. M. Ali, Tse, Daniel, Prabhakara, Shruthi, McLean, Cory, Steiner, Dave, Pilgrim, Rory, Kelly, Christopher, Azizi, Shekoofeh, Golden, Daniel
Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Building upon Gemini's multimodal models, we develop several models within
Externí odkaz:
http://arxiv.org/abs/2405.03162