Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Chaudhry Arslan"'
Large language models (LLMs) are increasingly employed in information-seeking and decision-making tasks. Despite their broad utility, LLMs tend to generate information that conflicts with real-world facts, and their persuasive style can make these in
Externí odkaz:
http://arxiv.org/abs/2409.12180
Publikováno v:
Frontiers in Environmental Chemistry, Vol 3 (2022)
Recent advances in graphene research have enabled the utilization of its nanocomposites for numerous energy-based and environmental applications. Recently, the advancement in graphene-based polymer nanocomposites has received much attention with spec
Externí odkaz:
https://doaj.org/article/4dbf921b5d07453b88a68270c80a8406
Autor:
Jurenka, Irina, Kunesch, Markus, McKee, Kevin R., Gillick, Daniel, Zhu, Shaojian, Wiltberger, Sara, Phal, Shubham Milind, Hermann, Katherine, Kasenberg, Daniel, Bhoopchand, Avishkar, Anand, Ankit, Pîslar, Miruna, Chan, Stephanie, Wang, Lisa, She, Jennifer, Mahmoudieh, Parsa, Rysbek, Aliya, Ko, Wei-Jen, Huber, Andrea, Wiltshire, Brett, Elidan, Gal, Rabin, Roni, Rubinovitz, Jasmin, Pitaru, Amit, McAllister, Mac, Wilkowski, Julia, Choi, David, Engelberg, Roee, Hackmon, Lidan, Levin, Adva, Griffin, Rachel, Sears, Michael, Bar, Filip, Mesar, Mia, Jabbour, Mana, Chaudhry, Arslan, Cohan, James, Thiagarajan, Sridhar, Levine, Nir, Brown, Ben, Gorur, Dilan, Grant, Svetlana, Hashimshoni, Rachel, Weidinger, Laura, Hu, Jieru, Chen, Dawn, Dolecki, Kuba, Akbulut, Canfer, Bileschi, Maxwell, Culp, Laura, Dong, Wen-Xin, Marchal, Nahema, Van Deman, Kelsie, Misra, Hema Bajaj, Duah, Michael, Ambar, Moran, Caciularu, Avi, Lefdal, Sandra, Summerfield, Chris, An, James, Kamienny, Pierre-Alexandre, Mohdi, Abhinit, Strinopoulous, Theofilos, Hale, Annie, Anderson, Wayne, Cobo, Luis C., Efron, Niv, Ananda, Muktha, Mohamed, Shakir, Heymans, Maureen, Ghahramani, Zoubin, Matias, Yossi, Gomes, Ben, Ibrahim, Lila
A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about the potential of new technologies to offer a personal tutor for every
Externí odkaz:
http://arxiv.org/abs/2407.12687
Publikováno v:
Geology, Ecology, and Landscapes, Vol 2, Iss 1, Pp 45-50 (2018)
Landfills and open dumping sites around the world are adding to the global warming issue. This is because of the existence of the main greenhouse gases in landfill gas (LFG); namely, methane (CH4) and carbon dioxide (CO2). The current study was focus
Externí odkaz:
https://doaj.org/article/e213c7c2a9ff40a392a377081e469a12
Autor:
Khurram Yousaf, Chen Kunjie, Chen Cairong, Adnan Abbas, Yuping Huang, Chaudhry Arslan, Zhang Xuejin
Publikováno v:
Journal of Food Quality, Vol 2017 (2017)
The response surface methodology was used to optimize the hydrothermal processing conditions based on the rice quality parameters of the Rong Youhua Zhan rice variety (Indica). The effect of soaking temperature (29.77, 40, 55, 70, and 80.23°C), soak
Externí odkaz:
https://doaj.org/article/78be1b6b19464fd088ddcd7770983cff
Publikováno v:
ICLR 2023
One of the main motivations of studying continual learning is that the problem setting allows a model to accrue knowledge from past tasks to learn new tasks more efficiently. However, recent studies suggest that the key metric that continual learning
Externí odkaz:
http://arxiv.org/abs/2303.08207
Autor:
Bornschein, Jorg, Galashov, Alexandre, Hemsley, Ross, Rannen-Triki, Amal, Chen, Yutian, Chaudhry, Arslan, He, Xu Owen, Douillard, Arthur, Caccia, Massimo, Feng, Qixuang, Shen, Jiajun, Rebuffi, Sylvestre-Alvise, Stacpoole, Kitty, Casas, Diego de las, Hawkins, Will, Lazaridou, Angeliki, Teh, Yee Whye, Rusu, Andrei A., Pascanu, Razvan, Ranzato, Marc'Aurelio
A shared goal of several machine learning communities like continual learning, meta-learning and transfer learning, is to design algorithms and models that efficiently and robustly adapt to unseen tasks. An even more ambitious goal is to build models
Externí odkaz:
http://arxiv.org/abs/2211.11747
Autor:
Chaudhry, Arslan, Menon, Aditya Krishna, Veit, Andreas, Jayasumana, Sadeep, Ramalingam, Srikumar, Kumar, Sanjiv
Publikováno v:
NeurIPS 2022 (First Workshop on Interpolation and Beyond)
Mixup is a regularization technique that artificially produces new samples using convex combinations of original training points. This simple technique has shown strong empirical performance, and has been heavily used as part of semi-supervised learn
Externí odkaz:
http://arxiv.org/abs/2210.16413
Autor:
Mirzadeh, Seyed Iman, Chaudhry, Arslan, Yin, Dong, Nguyen, Timothy, Pascanu, Razvan, Gorur, Dilan, Farajtabar, Mehrdad
A large body of research in continual learning is devoted to overcoming the catastrophic forgetting of neural networks by designing new algorithms that are robust to the distribution shifts. However, the majority of these works are strictly focused o
Externí odkaz:
http://arxiv.org/abs/2202.00275
Autor:
Asma Sattar, Chaudhry Arslan, Changying Ji, Sumiyya Sattar, Irshad Ali Mari, Haroon Rashid, Fariha Ilyas
Publikováno v:
Energies, Vol 9, Iss 3, p 198 (2016)
Three common pretreatments (mechanical, steam explosion and chemical) used to enhance the biodegradability of rice straw were compared on the basis of bio-hydrogen production potential while co-digesting rice straw with sludge under mesophilic (37 °
Externí odkaz:
https://doaj.org/article/0e2766689ef245f88d9ebb9dc5115526