Zobrazeno 1 - 10
of 962
pro vyhledávání: '"Gerstenberger P"'
Autor:
Chomutare, Taridzo, Babic, Aleksandar, Peltonen, Laura-Maria, Elunurm, Silja, Lundberg, Peter, Jönsson, Arne, Eneling, Emma, Gerstenberger, Ciprian-Virgil, Siggaard, Troels, Kolde, Raivo, Jerdhaf, Oskar, Hansson, Martin, Makhlysheva, Alexandra, Muzny, Miroslav, Ylipää, Erik, Brunak, Søren, Dalianis, Hercules
Background: Centralized collection and processing of healthcare data across national borders pose significant challenges, including privacy concerns, data heterogeneity and legal barriers. To address some of these challenges, we formed an interdiscip
Externí odkaz:
http://arxiv.org/abs/2409.17865
Autor:
Besta, Maciej, Gerstenberger, Robert, Iff, Patrick, Sonawane, Pournima, Luna, Juan Gómez, Kanakagiri, Raghavendra, Min, Rui, Kwaśniewski, Grzegorz, Mutlu, Onur, Hoefler, Torsten, Appuswamy, Raja, Mahony, Aidan O
Knowledge graphs (KGs) have achieved significant attention in recent years, particularly in the area of the Semantic Web as well as gaining popularity in other application domains such as data mining and search engines. Simultaneously, there has been
Externí odkaz:
http://arxiv.org/abs/2408.12173
Autor:
Besta, Maciej, Kubicek, Ales, Niggli, Roman, Gerstenberger, Robert, Weitzendorf, Lucas, Chi, Mingyuan, Iff, Patrick, Gajda, Joanna, Nyczyk, Piotr, Müller, Jürgen, Niewiadomski, Hubert, Chrapek, Marcin, Podstawski, Michał, Hoefler, Torsten
Retrieval Augmented Generation (RAG) enhances the abilities of Large Language Models (LLMs) by enabling the retrieval of documents into the LLM context to provide more accurate and relevant responses. Existing RAG solutions do not focus on queries th
Externí odkaz:
http://arxiv.org/abs/2406.05085
Autor:
Besta, Maciej, Paleari, Lorenzo, Kubicek, Ales, Nyczyk, Piotr, Gerstenberger, Robert, Iff, Patrick, Lehmann, Tomasz, Niewiadomski, Hubert, Hoefler, Torsten
Large Language Models (LLMs) are revolutionizing various domains, yet verifying their answers remains a significant challenge, especially for intricate open-ended tasks such as consolidation, summarization, and extraction of knowledge. In this work,
Externí odkaz:
http://arxiv.org/abs/2406.02524
Autor:
Besta, Maciej, Memedi, Florim, Zhang, Zhenyu, Gerstenberger, Robert, Piao, Guangyuan, Blach, Nils, Nyczyk, Piotr, Copik, Marcin, Kwaśniewski, Grzegorz, Müller, Jürgen, Gianinazzi, Lukas, Kubicek, Ales, Niewiadomski, Hubert, O'Mahony, Aidan, Mutlu, Onur, Hoefler, Torsten
The field of natural language processing (NLP) has witnessed significant progress in recent years, with a notable focus on improving large language models' (LLM) performance through innovative prompting techniques. Among these, prompt engineering cou
Externí odkaz:
http://arxiv.org/abs/2401.14295
During deep sleep and under anaesthesia spontaneous patterns of cortical activation frequently take the form of slow travelling waves. Slow wave sleep is an important cognitive state especially because of its relevance for memory consolidation. Howev
Externí odkaz:
http://arxiv.org/abs/2401.11008
Autor:
Besta, Maciej, Blach, Nils, Kubicek, Ales, Gerstenberger, Robert, Podstawski, Michal, Gianinazzi, Lukas, Gajda, Joanna, Lehmann, Tomasz, Niewiadomski, Hubert, Nyczyk, Piotr, Hoefler, Torsten
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence 2024 (AAAI'24)
We introduce Graph of Thoughts (GoT): a framework that advances prompting capabilities in large language models (LLMs) beyond those offered by paradigms such as Chain-of-Thought or Tree of Thoughts (ToT). The key idea and primary advantage of GoT is
Externí odkaz:
http://arxiv.org/abs/2308.09687
We introduce a Gaussian Prototype Layer for gradient-based prototype learning and demonstrate two novel network architectures for explainable segmentation one of which relies on region proposals. Both models are evaluated on agricultural datasets. Wh
Externí odkaz:
http://arxiv.org/abs/2306.14361
Autor:
Besta, Maciej, Gerstenberger, Robert, Fischer, Marc, Podstawski, Michał, Blach, Nils, Egeli, Berke, Mitenkov, Georgy, Chlapek, Wojciech, Michalewicz, Marek, Niewiadomski, Hubert, Müller, Jürgen, Hoefler, Torsten
Publikováno v:
Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2023 (SC '23)
Graph databases (GDBs) are crucial in academic and industry applications. The key challenges in developing GDBs are achieving high performance, scalability, programmability, and portability. To tackle these challenges, we harness established practice
Externí odkaz:
http://arxiv.org/abs/2305.11162
Autor:
David Jonathan Wasilko, Brian S. Gerstenberger, Kathleen A. Farley, Wei Li, Jennifer Alley, Mark E. Schnute, Ray J. Unwalla, Jorge Victorino, Kimberly K. Crouse, Ru Ding, Parag V. Sahasrabudhe, Fabien Vincent, Richard K. Frisbie, Alpay Dermenci, Andrew Flick, Chulho Choi, Gary Chinigo, James J. Mousseau, John I. Trujillo, Philippe Nuhant, Prolay Mondal, Vincent Lombardo, Daniel Lamb, Barbara J. Hogan, Gurdeep Singh Minhas, Elena Segala, Christine Oswald, Ian W. Windsor, Seungil Han, Mathieu Rappas, Robert M. Cooke, Matthew F. Calabrese, Gabriel Berstein, Atli Thorarensen, Huixian Wu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract The CC chemokine receptor 6 (CCR6) is a potential target for chronic inflammatory diseases. Previously, we reported an active CCR6 structure in complex with its cognate chemokine CCL20, revealing the molecular basis of CCR6 activation. Here,
Externí odkaz:
https://doaj.org/article/91af6bd491994266b492f68b0994ea6e
