Zobrazeno 1 - 10
of 1 343
pro vyhledávání: '"Accomazzi, A."'
Autor:
de Haan, Tijmen, Ting, Yuan-Sen, Ghosal, Tirthankar, Nguyen, Tuan Dung, Accomazzi, Alberto, Wells, Azton, Ramachandra, Nesar, Pan, Rui, Sun, Zechang
AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, and cosmology. Trained on the complete collection of astronomy-related arXiv papers from 2007-2024 along with millions of s
Externí odkaz:
http://arxiv.org/abs/2411.09012
Autor:
Pan, Rui, Nguyen, Tuan Dung, Arora, Hardik, Accomazzi, Alberto, Ghosal, Tirthankar, Ting, Yuan-Sen
Continual pretraining of large language models on domain-specific data has been proposed to enhance performance on downstream tasks. In astronomy, the previous absence of astronomy-focused benchmarks has hindered objective evaluation of these special
Externí odkaz:
http://arxiv.org/abs/2409.19750
Autor:
Iyer, Kartheik G., Yunus, Mikaeel, O'Neill, Charles, Ye, Christine, Hyk, Alina, McCormick, Kiera, Ciuca, Ioana, Wu, John F., Accomazzi, Alberto, Astarita, Simone, Chakrabarty, Rishabh, Cranney, Jesse, Field, Anjalie, Ghosal, Tirthankar, Ginolfi, Michele, Huertas-Company, Marc, Jablonska, Maja, Kruk, Sandor, Liu, Huiling, Marchidan, Gabriel, Mistry, Rohit, Naiman, J. P., Peek, J. E. G., Polimera, Mugdha, Rodriguez, Sergio J., Schawinski, Kevin, Sharma, Sanjib, Smith, Michael J., Ting, Yuan-Sen, Walmsley, Mike
The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable lite
Externí odkaz:
http://arxiv.org/abs/2408.01556
Autor:
Ting, Yuan-Sen, Nguyen, Tuan Dung, Ghosal, Tirthankar, Pan, Rui, Arora, Hardik, Sun, Zechang, de Haan, Tijmen, Ramachandra, Nesar, Wells, Azton, Madireddy, Sandeep, Accomazzi, Alberto
We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy an
Externí odkaz:
http://arxiv.org/abs/2407.11194
Autor:
Bhattacharjee, Bishwaranjan, Trivedi, Aashka, Muraoka, Masayasu, Ramasubramanian, Muthukumaran, Udagawa, Takuma, Gurung, Iksha, Pantha, Nishan, Zhang, Rong, Dandala, Bharath, Ramachandran, Rahul, Maskey, Manil, Bugbee, Kaylin, Little, Mike, Fancher, Elizabeth, Gerasimov, Irina, Mehrabian, Armin, Sanders, Lauren, Costes, Sylvain, Blanco-Cuaresma, Sergi, Lockhart, Kelly, Allen, Thomas, Grezes, Felix, Ansdell, Megan, Accomazzi, Alberto, El-Kurdi, Yousef, Wertheimer, Davis, Pfitzmann, Birgit, Ramis, Cesar Berrospi, Dolfi, Michele, de Lima, Rafael Teixeira, Vagenas, Panagiotis, Mukkavilli, S. Karthik, Staar, Peter, Vahidinia, Sanaz, McGranaghan, Ryan, Lee, Tsendgar
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs trained using domain-focused corpora perform better on specialized tasks
Externí odkaz:
http://arxiv.org/abs/2405.10725
The Astrophysics Source Code Library (ASCL) is a free online registry for source codes of interest to astronomers, astrophysicists, and planetary scientists. It lists, and in some cases houses, software that has been used in research appearing in or
Externí odkaz:
http://arxiv.org/abs/2312.17297
Autor:
Blanco-Cuaresma, Sergi, Ciucă, Ioana, Accomazzi, Alberto, Kurtz, Michael J., Henneken, Edwin A., Lockhart, Kelly E., Grezes, Felix, Allen, Thomas, Shapurian, Golnaz, Grant, Carolyn S., Thompson, Donna M., Hostetler, Timothy W., Templeton, Matthew R., Chen, Shinyi, Koch, Jennifer, Jacovich, Taylor, Chivvis, Daniel, Alves, Fernanda de Macedo, Paquin, Jean-Claude, Bartlett, Jennifer, Polimera, Mugdha, Jarmak, Stephanie
Open-source Large Language Models enable projects such as NASA SciX (i.e., NASA ADS) to think out of the box and try alternative approaches for information retrieval and data augmentation, while respecting data copyright and users' privacy. However,
Externí odkaz:
http://arxiv.org/abs/2312.14211
The automatic identification of planetary feature names in astronomy publications presents numerous challenges. These features include craters, defined as roughly circular depressions resulting from impact or volcanic activity; dorsas, which are elon
Externí odkaz:
http://arxiv.org/abs/2312.08579
Autor:
Blanton, Michael R., Evans, Janet D., Norman, Dara, O'Mullane, William, Price-Whelan, Adrian, Rizzi, Luca, Accomazzi, Alberto, Ansdell, Megan, Bailey, Stephen, Barrett, Paul, Berukoff, Steven, Bolton, Adam, Borrill, Julian, Cruz, Kelle, Dalcanton, Julianne, Desai, Vandana, Dubois-Felsmann, Gregory P., Economou, Frossie, Ferguson, Henry, Field, Bryan, Foreman-Mackey, Dan, Forero-Romero, Jaime, Gaffney, Niall, Gillies, Kim, Graham, Matthew J., Gwyn, Steven, Hennawi, Joseph, Hughes, Anna L. H., Jaffe, Tess, Jagannathan, Preshanth, Jenness, Tim, Jurić, Mario, Kavelaars, JJ, Kee, Kerk, Kern, Jeff, Kremin, Anthony, Labrie, Kathleen, Lacy, Mark, Law, Casey, Martínez-Galarza, Rafael, McCully, Curtis, McEnery, Julie, Miller, Bryan, Moriarty, Christopher, Muench, August, Muna, Demitri, Murillo, Angela, Narayan, Gautham, Neill, James D., Nikutta, Robert, Ojha, Roopesh, Olsen, Knut, O'Meara, John, Rusholme, Ben, Seaman, Robert, Starkman, Nathaniel, Still, Martin, Stoehr, Felix, Swinbank, John D., Teuben, Peter, Toledo, Ignacio, Tollerud, Erik, Turk, Matthew D., Turner, James, Vacca, William, Vieira, Joaquin, Weaver, Benjamin, Weiner, Benjamin, Weiss, Jason, Westfall, Kyle, Willman, Beth, Zhao, Lily
The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and combining archives of data. To address this challenge, we propose the
Externí odkaz:
http://arxiv.org/abs/2311.04272
Autor:
Nguyen, Tuan Dung, Ting, Yuan-Sen, Ciucă, Ioana, O'Neill, Charlie, Sun, Ze-Chang, Jabłońska, Maja, Kruk, Sandor, Perkowski, Ernest, Miller, Jack, Li, Jason, Peek, Josh, Iyer, Kartheik, Różański, Tomasz, Khetarpal, Pranav, Zaman, Sharaf, Brodrick, David, Méndez, Sergio J. Rodríguez, Bui, Thang, Goodman, Alyssa, Accomazzi, Alberto, Naiman, Jill, Cranney, Jesse, Schawinski, Kevin, UniverseTBD
Large language models excel in many human-language tasks but often falter in highly specialized domains like scholarly astronomy. To bridge this gap, we introduce AstroLLaMA, a 7-billion-parameter model fine-tuned from LLaMA-2 using over 300,000 astr
Externí odkaz:
http://arxiv.org/abs/2309.06126