Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Gerstenberger, Robert"'
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
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
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:
BESTA, MACIEJ1 maciej.besta@inf.ethz.ch, GERSTENBERGER, ROBERT1 robert@gmail.com, PETER, EMANUEL1 peterem@student.ethz.ch, FISCHER, MARC2 marc.fischer@prodyna.com, PODSTAWSKI, MICHAŁ3 mpodstawski@gmail.com, BARTHELS, CLAUDE1 claudeb@inf.ethz.ch, ALONSO, GUSTAVO1 alonso@inf.ethz.ch, HOEFLER, TORSTEN1 torsten.hoefler@inf.ethz.ch
Publikováno v:
ACM Computing Surveys. Feb2024, Vol. 56 Issue 2, p1-40. 40p.
Publikováno v:
Proceedings of the ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis, pages 53:1--53:12, November 2013
Modern interconnects offer remote direct memory access (RDMA) features. Yet, most applications rely on explicit message passing for communications albeit their unwanted overheads. The MPI-3.0 standard defines a programming interface for exploiting RD
Externí odkaz:
http://arxiv.org/abs/2001.07747
Autor:
Besta, Maciej, Weber, Simon, Gianinazzi, Lukas, Gerstenberger, Robert, Ivanov, Andrey, Oltchik, Yishai, Hoefler, Torsten
Publikováno v:
Proceedings of the ACM/IEEE International Conference on High Performance Computing, Networking, Storage and Analysis (SC19), November 2020. Best Paper Finalist, Best Student Paper Finalist
We propose Slim Graph: the first programming model and framework for practical lossy graph compression that facilitates high-performance approximate graph processing, storage, and analytics. Slim Graph enables the developer to express numerous compre
Externí odkaz:
http://arxiv.org/abs/1912.08950
Autor:
Besta, Maciej, Gerstenberger, Robert, Peter, Emanuel, Fischer, Marc, Podstawski, Michał, Barthels, Claude, Alonso, Gustavo, Hoefler, Torsten
Graph processing has become an important part of multiple areas of computer science, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Numerous graphs such as web or social networks may
Externí odkaz:
http://arxiv.org/abs/1910.09017
Autor:
Gerstenberger, Robert1 robertge@inf.ethz.ch, Besta, Maciej1 maciej.besta@inf.ethz.ch, Hoefler, Torsten1 htor@inf.ethz.ch
Publikováno v:
Communications of the ACM. Oct2018, Vol. 61 Issue 10, p108-113. 8p. 2 Diagrams, 4 Graphs.