Zobrazeno 1 - 10
of 47 662
pro vyhledávání: '"A Sadat"'
Autor:
Zahraei, Pardis Sadat, Shakeri, Zahra
Biased AI-generated medical advice and misdiagnoses can jeopardize patient safety, making the integrity of AI in healthcare more critical than ever. As Large Language Models (LLMs) take on a growing role in medical decision-making, addressing their b
Externí odkaz:
http://arxiv.org/abs/2410.06566
We present TuringQ, the first benchmark designed to evaluate the reasoning capabilities of large language models (LLMs) in the theory of computation. TuringQ consists of 4,006 undergraduate and graduate-level question-answer pairs, categorized into f
Externí odkaz:
http://arxiv.org/abs/2410.06547
Classifier-free guidance (CFG) is crucial for improving both generation quality and alignment between the input condition and final output in diffusion models. While a high guidance scale is generally required to enhance these aspects, it also causes
Externí odkaz:
http://arxiv.org/abs/2410.02416
Breast cancer is a disease in which cells in the breast grow out of control. After surgery, chemotherapy, and other invasive treatments, hyperthermia is a suitable choice with the minimal side effects. In this paper, the treatment of breast cancer us
Externí odkaz:
http://arxiv.org/abs/2410.00058
The optical manipulation of magnon states in antiferromagnets (AFMs) holds significant potential for advancing AFM-based computing devices. In particular, two-magnon Raman scattering processes are known to generate entangled magnon-pairs with opposit
Externí odkaz:
http://arxiv.org/abs/2409.10659
Autor:
Liang, Guojun, Abiri, Najmeh, Hashemi, Atiye Sadat, Lundström, Jens, Byttner, Stefan, Tiwari, Prayag
Accurate imputation is essential for the reliability and success of downstream tasks. Recently, diffusion models have attracted great attention in this field. However, these models neglect the latent distribution in a lower-dimensional space derived
Externí odkaz:
http://arxiv.org/abs/2409.08917
This paper explores the intersection of psychology and artificial intelligence through the development and evaluation of specialized Large Language Models (LLMs). We introduce PsychoLex, a suite of resources designed to enhance LLMs' proficiency in p
Externí odkaz:
http://arxiv.org/abs/2408.08848
We consider certain random matrix eigenvalue dynamics, akin to Dyson Brownian motion, introduced by Rider and Valko. We show that from every initial condition, including ones involving coinciding coordinates, the dynamics, enhanced with more informat
Externí odkaz:
http://arxiv.org/abs/2408.00717
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Alizadeh, Hadi, Taghavi, Zeinab Sadat, Sameti, Hossein
Publikováno v:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Semantic Textual Relatedness holds significant relevance in Natural Language Processing, finding applications across various domains. Traditionally, approaches to STR have relied on knowledge-based and statistical methods. However, with the emergence
Externí odkaz:
http://arxiv.org/abs/2407.12426
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Qazvini, Arian, Sadeghi, Pouya, Taghavi, Zeinab Sadat, Sameti, Hossein
Detecting Machine-Generated Text (MGT) has emerged as a significant area of study within Natural Language Processing. While language models generate text, they often leave discernible traces, which can be scrutinized using either traditional feature-
Externí odkaz:
http://arxiv.org/abs/2407.11774