Zobrazeno 1 - 10
of 16 321
pro vyhledávání: '"Kazim, A"'
Autor:
Vit, Aycan Deniz, Rzayev, Ujal, Danis, Bahrem Serhat, Amiri, Ali Najjar, Gorgulu, Kazim, Magden, Emir Salih
We propose a novel design paradigm for arbitrarily capable deep photonic networks of cascaded Mach-Zehnder Interferometers (MZIs) for on-chip universal polarization handling. Using a device architecture made of cascaded Mach-Zehnder interferometers,
Externí odkaz:
http://arxiv.org/abs/2411.16698
Open-generation bias benchmarks evaluate social biases in Large Language Models (LLMs) by analyzing their outputs. However, the classifiers used in analysis often have inherent biases, leading to unfair conclusions. This study examines such biases in
Externí odkaz:
http://arxiv.org/abs/2410.11059
Quantum image representation (QIR) is a key challenge in quantum image processing (QIP) due to the large number of pixels in images, which increases the need for quantum gates and qubits. However, current quantum systems face limitations in run-time
Externí odkaz:
http://arxiv.org/abs/2409.14629
Stereotypes are generalised assumptions about societal groups, and even state-of-the-art LLMs using in-context learning struggle to identify them accurately. Due to the subjective nature of stereotypes, where what constitutes a stereotype can vary wi
Externí odkaz:
http://arxiv.org/abs/2409.11579
Autor:
Liang, Mengfei, Arun, Archish, Wu, Zekun, Munoz, Cristian, Lutch, Jonathan, Kazim, Emre, Koshiyama, Adriano, Treleaven, Philip
Hallucination, the generation of factually incorrect content, is a growing challenge in Large Language Models (LLMs). Existing detection and mitigation methods are often isolated and insufficient for domain-specific needs, lacking a standardized pipe
Externí odkaz:
http://arxiv.org/abs/2409.11353
Autor:
Guan, Xin, Demchak, Nathaniel, Gupta, Saloni, Wang, Ze, Ertekin Jr., Ediz, Koshiyama, Adriano, Kazim, Emre, Wu, Zekun
Publikováno v:
COLING 2025 Main Conference
The development of unbiased large language models is widely recognized as crucial, yet existing benchmarks fall short in detecting biases due to limited scope, contamination, and lack of a fairness baseline. SAGED(bias) is the first holistic benchmar
Externí odkaz:
http://arxiv.org/abs/2409.11149
Autor:
Jain, Navya, Wu, Zekun, Munoz, Cristian, Hilliard, Airlie, Koshiyama, Adriano, Kazim, Emre, Treleaven, Philip
As the demand for human-like interactions with LLMs continues to grow, so does the interest in manipulating their personality traits, which has emerged as a key area of research. Methods like prompt-based In-Context Knowledge Editing (IKE) and gradie
Externí odkaz:
http://arxiv.org/abs/2409.10245
Our main objective in this paper (which is expository for the most part) is to study the necessary steps to prove a factorization formula for a certain triple product $p$-adic $L$-function guided by the Artin formalism. The key ingredients are: a) th
Externí odkaz:
http://arxiv.org/abs/2409.08645
Artificial intelligence (AI) signals the beginning of a revolutionary period where technological advancement and social change interact to completely reshape economies, work paradigms, and industries worldwide. This essay addresses the opportunities
Externí odkaz:
http://arxiv.org/abs/2409.10541
Autor:
Jabbar, Abdul, Kazim, Jalil Ur-Rehman, Shawky, Mahmoud A., Imran, Muhammad Ali, Abbasi, Qammer, Ur-Rehman, Masood
This paper presents the design and comprehensive measurements of a compact high-gain 32 element planar antenna array covering the n257 (26.5-29.5 GHz) millimeter wave (mmWave) band. First an 8-element quasi-uniform linear array is designed using a se
Externí odkaz:
http://arxiv.org/abs/2407.09944