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pro vyhledávání: '"A., Divya"'
Informed by the success of the transformer model in various computer vision tasks, we design an end-to-end trainable model for the automatic detection and classification of bleeding and non-bleeding frames extracted from Wireless Capsule Endoscopy (W
Externí odkaz:
http://arxiv.org/abs/2412.19218
This study aims to determine the algebraic structures of $\alpha$-constacyclic codes of length $3p^s$ over the finite commutative non-chain ring $\mathcal{R}=\frac{\mathbb{F}_{p^m}[u, v]}{\langle u^2, v^2, uv-vu\rangle}$, for a prime $p \neq 3.$ For
Externí odkaz:
http://arxiv.org/abs/2412.17697
The large size of DNNs poses a significant challenge for deployment on devices with limited resources, such as mobile, edge, and IoT platforms. To address this issue, a distributed inference framework can be utilized. In this framework, a small-scale
Externí odkaz:
http://arxiv.org/abs/2412.16616
Autor:
LearnLM Team, Modi, Abhinit, Veerubhotla, Aditya Srikanth, Rysbek, Aliya, Huber, Andrea, Wiltshire, Brett, Veprek, Brian, Gillick, Daniel, Kasenberg, Daniel, Ahmed, Derek, Jurenka, Irina, Cohan, James, She, Jennifer, Wilkowski, Julia, Alarakyia, Kaiz, McKee, Kevin R., Wang, Lisa, Kunesch, Markus, Schaekermann, Mike, Pîslar, Miruna, Joshi, Nikhil, Mahmoudieh, Parsa, Jhun, Paul, Wiltberger, Sara, Mohamed, Shakir, Agarwal, Shashank, Phal, Shubham Milind, Lee, Sun Jae, Strinopoulos, Theofilos, Ko, Wei-Jen, Wang, Amy, Anand, Ankit, Bhoopchand, Avishkar, Wild, Dan, Pandya, Divya, Bar, Filip, Graham, Garth, Winnemoeller, Holger, Nagda, Mahvish, Kolhar, Prateek, Schneider, Renee, Zhu, Shaojian, Chan, Stephanie, Yadlowsky, Steve, Sounderajah, Viknesh, Assael, Yannis
Today's generative AI systems are tuned to present information by default rather than engage users in service of learning as a human tutor would. To address the wide range of potential education use cases for these systems, we reframe the challenge o
Externí odkaz:
http://arxiv.org/abs/2412.16429
Autor:
Chiang, Erica, Shanmugam, Divya, Beecy, Ashley N., Sayer, Gabriel, Uriel, Nir, Estrin, Deborah, Garg, Nikhil, Pierson, Emma
Disease progression models are widely used to inform the diagnosis and treatment of many progressive diseases. However, a significant limitation of existing models is that they do not account for health disparities that can bias the observed data. To
Externí odkaz:
http://arxiv.org/abs/2412.16406
Let $p$ be an odd prime. In this paper, we have determined the Hamming distances for constacyclic codes of length $2p^s$ over the finite commutative non-chain ring $\mathcal{R}=\frac{\mathbb{F}_{p^m}[u, v]}{\langle u^2, v^2, uv-vu\rangle}$. Also thei
Externí odkaz:
http://arxiv.org/abs/2412.16043
Autor:
Wadhwa, Sahil, Xu, Chengtian, Chen, Haoming, Mahalingam, Aakash, Kar, Akankshya, Chaudhary, Divya
Publikováno v:
The First Workshop on Multilingual Counterspeech Generation (MCG) at The 31st International Conference on Computational Linguistics (COLING 2025)
The automatic generation of counter-speech (CS) is a critical strategy for addressing hate speech by providing constructive and informed responses. However, existing methods often fail to generate high-quality, impactful, and scalable CS, particularl
Externí odkaz:
http://arxiv.org/abs/2412.15453
Publikováno v:
Workshop on Generative AI and Knowledge Graphs (GenAIK) at The 31st International Conference on Computational Linguistics (COLING 2025)
Retrieval-Augmented Generation (RAG) systems have become pivotal in leveraging vast corpora to generate informed and contextually relevant responses, notably reducing hallucinations in Large Language Models. Despite significant advancements, these sy
Externí odkaz:
http://arxiv.org/abs/2412.15443
Autor:
Demarne, Mathieu, Cilimdzic, Miso, Falkowski, Tom, Johnson, Timothy, Gramling, Jim, Kuang, Wei, Hou, Hoobie, Aryan, Amjad, Subramaniam, Gayatri, Lee, Kenny, Mejia, Manuel, Liu, Lisa, Vermareddy, Divya
We present ARCAS (Automated Root Cause Analysis System), a diagnostic platform based on a Domain Specific Language (DSL) built for fast diagnostic implementation and low learning curve. Arcas is composed of a constellation of automated troubleshootin
Externí odkaz:
http://arxiv.org/abs/2412.15374
Land-use and land cover (LULC) analysis is critical in remote sensing, with wide-ranging applications across diverse fields such as agriculture, utilities, and urban planning. However, automating LULC map generation using machine learning is rendered
Externí odkaz:
http://arxiv.org/abs/2412.12552