Zobrazeno 1 - 10
of 59 750
pro vyhledávání: '"Eren, A."'
Autor:
Ozbay, Eren
This paper offers a comprehensive analysis of collaborative bandit algorithms and provides a thorough comparison of their performance. Collaborative bandits aim to improve the performance of contextual bandits by introducing relationships between arm
Externí odkaz:
http://arxiv.org/abs/2410.12086
Autor:
Jantos, Thomas, Scheiber, Martin, Brommer, Christian, Allak, Eren, Weiss, Stephan, Steinbrener, Jan
Object-relative mobile robot navigation is essential for a variety of tasks, e.g. autonomous critical infrastructure inspection, but requires the capability to extract semantic information about the objects of interest from raw sensory data. While de
Externí odkaz:
http://arxiv.org/abs/2410.05996
Autor:
Barron, Ryan C., Grantcharov, Ves, Wanna, Selma, Eren, Maksim E., Bhattarai, Manish, Solovyev, Nicholas, Tompkins, George, Nicholas, Charles, Rasmussen, Kim Ø., Matuszek, Cynthia, Alexandrov, Boian S.
Large Language Models (LLMs) are pre-trained on large-scale corpora and excel in numerous general natural language processing (NLP) tasks, such as question answering (QA). Despite their advanced language capabilities, when it comes to domain-specific
Externí odkaz:
http://arxiv.org/abs/2410.02721
Publikováno v:
ACM AI in Finance Conference ICAIF 2024
Adoption of AI by criminal entities across traditional and emerging financial crime paradigms has been a disturbing recent trend. Particularly concerning is the proliferation of generative AI, which has empowered criminal activities ranging from soph
Externí odkaz:
http://arxiv.org/abs/2410.09066
Autor:
Mittu, Fazal, Bu, Yihuan, Gupta, Akshat, Devireddy, Ashok, Ozdarendeli, Alp Eren, Singh, Anant, Anumanchipalli, Gopala
While the language modeling objective has been shown to be deeply connected with compression, it is surprising that modern LLMs are not employed in practical text compression systems. In this paper, we provide an in-depth analysis of neural network a
Externí odkaz:
http://arxiv.org/abs/2409.17141
In this technical report, we document the changes we made to SDXL in the process of training NovelAI Diffusion V3, our state of the art anime image generation model.
Comment: 14 pages, 8 figures
Comment: 14 pages, 8 figures
Externí odkaz:
http://arxiv.org/abs/2409.15997
Autor:
Emma, Philip, Kurshan, Eren
Publikováno v:
IBM Journal of Research and Development, Volume 52, Pages 541-552, 2008/11
The semiconductor industry is reaching a fascinating confluence in several evolutionary trends that will likely lead to a number of revolutionary changes in how computer systems are designed, implemented, scaled, and used. Since Moores Law, which has
Externí odkaz:
http://arxiv.org/abs/2409.14527
Autor:
Emma, Philip, Kurshan, Eren
Publikováno v:
In Proceedings of 2010 IEEE International Interconnect Technology Conference. IEEE, 2010. p. 1-3
3D promises a new dimension in composing systems by aggregating chips. Literally. While the most common uses are still tightly connected with its early forms as a packaging technology, new application domains have been emerging. As the underlying tec
Externí odkaz:
http://arxiv.org/abs/2409.09068
Partitioning is a known problem in computer science and is critical in chip design workflows, as advancements in this area can significantly influence design quality and efficiency. Deep Learning (DL) techniques, particularly those involving Graph Ne
Externí odkaz:
http://arxiv.org/abs/2409.01387
Autor:
Moon, Suhong, Jha, Siddharth, Erdogan, Lutfi Eren, Kim, Sehoon, Lim, Woosang, Keutzer, Kurt, Gholami, Amir
Recent advancements in function calling and tool use have significantly enhanced the capabilities of large language models (LLMs) by enabling them to interact with external information sources and execute complex tasks. However, the limited context w
Externí odkaz:
http://arxiv.org/abs/2409.02141