Zobrazeno 1 - 10
of 631
pro vyhledávání: '"Fernández, Ivan"'
Recent research has shown that large language models (LLMs) are particularly vulnerable to adversarial attacks. Since the release of ChatGPT, various industries are adopting LLM-based chatbots and virtual assistants in their data workflows. The rapid
Externí odkaz:
http://arxiv.org/abs/2412.06788
Autor:
Fernandez, Ivan A., Neupane, Subash, Chakraborty, Trisha, Mitra, Shaswata, Mittal, Sudip, Pillai, Nisha, Chen, Jingdao, Rahimi, Shahram
Industry 4.0 has witnessed the rise of complex robots fueled by the integration of Artificial Intelligence/Machine Learning (AI/ML) and Digital Twin (DT) technologies. While these technologies offer numerous benefits, they also introduce potential pr
Externí odkaz:
http://arxiv.org/abs/2406.18812
Autor:
Giannoula, Christina, Yang, Peiming, Fernandez, Ivan, Yang, Jiacheng, Durvasula, Sankeerth, Li, Yu Xin, Sadrosadati, Mohammad, Luna, Juan Gomez, Mutlu, Onur, Pekhimenko, Gennady
Graph Neural Networks (GNNs) are emerging ML models to analyze graph-structure data. Graph Neural Network (GNN) execution involves both compute-intensive and memory-intensive kernels, the latter dominates the total time, being significantly bottlenec
Externí odkaz:
http://arxiv.org/abs/2402.16731
This paper proposes the use of Large Language Models (LLMs) for translating Request for Comments (RFC) protocol specifications into a format compatible with the Cryptographic Protocol Shapes Analyzer (CPSA). This novel approach aims to reduce the com
Externí odkaz:
http://arxiv.org/abs/2402.00890
Autor:
Neupane, Subash, Mitra, Shaswata, Fernandez, Ivan A., Saha, Swayamjit, Mittal, Sudip, Chen, Jingdao, Pillai, Nisha, Rahimi, Shahram
Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from robotic vacuum cleaners to semi-autonomous cars. These systems are bu
Externí odkaz:
http://arxiv.org/abs/2310.08565
Generative Artificial Intelligence (GenAI) has emerged as a powerful technology capable of autonomously producing highly realistic content in various domains, such as text, images, audio, and videos. With its potential for positive applications in cr
Externí odkaz:
http://arxiv.org/abs/2306.13033
Sparse matrix computation is crucial in various modern applications, including large-scale graph analytics, deep learning, and recommender systems. The performance of sparse kernels varies greatly depending on the structure of the input matrix, makin
Externí odkaz:
http://arxiv.org/abs/2304.06944
Autor:
Neupane, Subash, Fernandez, Ivan A., Patterson, Wilson, Mittal, Sudip, Parmar, Milan, Rahimi, Shahram
Vehicles are complex Cyber Physical Systems (CPS) that operate in a variety of environments, and the likelihood of failure of one or more subsystems, such as the engine, transmission, brakes, and fuel, can result in unscheduled downtime and incur hig
Externí odkaz:
http://arxiv.org/abs/2302.00152
Autor:
Ghiasi, Nika Mansouri, Vijaykumar, Nandita, Oliveira, Geraldo F., Orosa, Lois, Fernandez, Ivan, Sadrosadati, Mohammad, Kanellopoulos, Konstantinos, Hajinazar, Nastaran, Luna, Juan Gómez, Mutlu, Onur
Partitioning applications between NDP and host CPU cores causes inter-segment data movement overhead, which is caused by moving data generated from one segment (e.g., instructions, functions) and used in consecutive segments. Prior works take two app
Externí odkaz:
http://arxiv.org/abs/2212.06292
Autor:
Fernandez, Ivan, Giannoula, Christina, Manglik, Aditya, Quislant, Ricardo, Ghiasi, Nika Mansouri, Gómez-Luna, Juan, Gutierrez, Eladio, Plata, Oscar, Mutlu, Onur
Publikováno v:
IEEE Access, vol. 12, pp. 36727-36742, 2024
Time Series Analysis (TSA) is a critical workload to extract valuable information from collections of sequential data, e.g., detecting anomalies in electrocardiograms. Subsequence Dynamic Time Warping (sDTW) is the state-of-the-art algorithm for high
Externí odkaz:
http://arxiv.org/abs/2211.04369