Zobrazeno 1 - 10
of 31 425
pro vyhledávání: '"More, A. A."'
Strongly lensed type Ia supernovae (SNe Ia) provide a unique cosmological probe to address the Hubble tension problem in cosmology. In addition to the sensitivity of the time delays to the value of the Hubble constant, the transient and standard cand
Externí odkaz:
http://arxiv.org/abs/2411.09412
Learning-based solutions for long-tailed recognition face difficulties in generalizing on balanced test datasets. Due to imbalanced data prior, the learned \textit{a posteriori} distribution is biased toward the most frequent (head) classes, leading
Externí odkaz:
http://arxiv.org/abs/2412.16540
Autor:
Addison, Parker, Nguyen, Minh-Tuan H., Medan, Tomislav, Shah, Jinali, Manzari, Mohammad T., McElrone, Brendan, Lalwani, Laksh, More, Aboli, Sharma, Smita, Roth, Holger R., Yang, Isaac, Chen, Chester, Xu, Daguang, Cheng, Yan, Feng, Andrew, Xu, Ziyue
Organizations seeking to utilize Large Language Models (LLMs) for knowledge querying and analysis often encounter challenges in maintaining an LLM fine-tuned on targeted, up-to-date information that keeps answers relevant and grounded. Retrieval Augm
Externí odkaz:
http://arxiv.org/abs/2412.13163
Autor:
Bradbury, Jeremy S., More, Riddhi
The use of large language models (LLMs) is widespread across many domains, including Software Engineering, where they have been used to automate tasks such as program generation and test classification. As LLM-based methods continue to evolve, it is
Externí odkaz:
http://arxiv.org/abs/2412.01526
Autor:
Vayani, Ashmal, Dissanayake, Dinura, Watawana, Hasindri, Ahsan, Noor, Sasikumar, Nevasini, Thawakar, Omkar, Ademtew, Henok Biadglign, Hmaiti, Yahya, Kumar, Amandeep, Kuckreja, Kartik, Maslych, Mykola, Ghallabi, Wafa Al, Mihaylov, Mihail, Qin, Chao, Shaker, Abdelrahman M, Zhang, Mike, Ihsani, Mahardika Krisna, Esplana, Amiel, Gokani, Monil, Mirkin, Shachar, Singh, Harsh, Srivastava, Ashay, Hamerlik, Endre, Izzati, Fathinah Asma, Maani, Fadillah Adamsyah, Cavada, Sebastian, Chim, Jenny, Gupta, Rohit, Manjunath, Sanjay, Zhumakhanova, Kamila, Rabevohitra, Feno Heriniaina, Amirudin, Azril, Ridzuan, Muhammad, Kareem, Daniya, More, Ketan, Li, Kunyang, Shakya, Pramesh, Saad, Muhammad, Ghasemaghaei, Amirpouya, Djanibekov, Amirbek, Azizov, Dilshod, Jankovic, Branislava, Bhatia, Naman, Cabrera, Alvaro, Obando-Ceron, Johan, Otieno, Olympiah, Farestam, Fabian, Rabbani, Muztoba, Baliah, Sanoojan, Sanjeev, Santosh, Shtanchaev, Abduragim, Fatima, Maheen, Nguyen, Thao, Kareem, Amrin, Aremu, Toluwani, Xavier, Nathan, Bhatkal, Amit, Toyin, Hawau, Chadha, Aman, Cholakkal, Hisham, Anwer, Rao Muhammad, Felsberg, Michael, Laaksonen, Jorma, Solorio, Thamar, Choudhury, Monojit, Laptev, Ivan, Shah, Mubarak, Khan, Salman, Khan, Fahad
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cultural contexts, respect local sensitivities, and support low-resource
Externí odkaz:
http://arxiv.org/abs/2411.16508
In an effort to mitigate the harms of large language models (LLMs), learning from human feedback (LHF) has been used to steer LLMs towards outputs that are intended to be both less harmful and more helpful. Despite the widespread adoption of LHF in p
Externí odkaz:
http://arxiv.org/abs/2411.08243
Autor:
Thakkar, Megh, More, Yash, Fournier, Quentin, Riemer, Matthew, Chen, Pin-Yu, Zouaq, Amal, Das, Payel, Chandar, Sarath
There is a growing interest in training domain-expert LLMs that excel in specific technical fields compared to their general-purpose instruction-tuned counterparts. However, these expert models often experience a loss in their safety abilities in the
Externí odkaz:
http://arxiv.org/abs/2411.06824
Autor:
Abe, Katsuya T., Oguri, Masamune, Birrer, Simon, Khadka, Narayan, Marshall, Philip J., Lemon, Cameron, More, Anupreeta, Collaboration, the LSST Dark Energy Science
Time delays in both galaxy- and cluster-scale strong gravitational lenses have recently attracted a lot of attention in the context of the Hubble tension. Future wide-field cadenced surveys, such as the LSST, are anticipated to discover strong lenses
Externí odkaz:
http://arxiv.org/abs/2411.07509
Combining neural networks with galaxy light subtraction for discovering strong lenses in the HSC SSP
Galaxy-scale strong gravitational lenses are valuable objects for a variety of astrophysical and cosmological applications. Strong lensing galaxies are rare, so efficient search methods, such as convolutional neural networks, are often used on large
Externí odkaz:
http://arxiv.org/abs/2411.07492
Human-computer interaction (HCI) has been a widely researched area for many years, with continuous advancements in technology leading to the development of new techniques that change the way we interact with computers. With the recent advent of power
Externí odkaz:
http://arxiv.org/abs/2411.04263