Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Autor: Zimmermann, Yoel, Bazgir, Adib, Afzal, Zartashia, Agbere, Fariha, Ai, Qianxiang, Alampara, Nawaf, Al-Feghali, Alexander, Ansari, Mehrad, Antypov, Dmytro, Aswad, Amro, Bai, Jiaru, Baibakova, Viktoriia, Biswajeet, Devi Dutta, Bitzek, Erik, Bocarsly, Joshua D., Borisova, Anna, Bran, Andres M, Brinson, L. Catherine, Calderon, Marcel Moran, Canalicchio, Alessandro, Chen, Victor, Chiang, Yuan, Circi, Defne, Charmes, Benjamin, Chaudhary, Vikrant, Chen, Zizhang, Chiu, Min-Hsueh, Clymo, Judith, Dabhadkar, Kedar, Daelman, Nathan, Datar, Archit, Evans, Matthew L., Fard, Maryam Ghazizade, Fisicaro, Giuseppe, Gangan, Abhijeet Sadashiv, George, Janine, Gonzalez, Jose D. Cojal, Götte, Michael, Gupta, Ankur K., Harb, Hassan, Hong, Pengyu, Ibrahim, Abdelrahman, Ilyas, Ahmed, Imran, Alishba, Ishimwe, Kevin, Issa, Ramsey, Jablonka, Kevin Maik, Jones, Colin, Josephson, Tyler R., Juhasz, Greg, Kapoor, Sarthak, Kang, Rongda, Khalighinejad, Ghazal, Khan, Sartaaj, Klawohn, Sascha, Kuman, Suneel, Ladines, Alvin Noe, Leang, Sarom, Lederbauer, Magdalena, Liao, Sheng-Lun Mark, Liu, Hao, Liu, Xuefeng, Lo, Stanley, Madireddy, Sandeep, Maharana, Piyush Ranjan, Maheshwari, Shagun, Mahjoubi, Soroush, Márquez, José A., Mills, Rob, Mohanty, Trupti, Mohr, Bernadette, Moosavi, Seyed Mohamad, Moßhammer, Alexander, Naghdi, Amirhossein D., Naik, Aakash, Narykov, Oleksandr, Näsström, Hampus, Nguyen, Xuan Vu, Ni, Xinyi, O'Connor, Dana, Olayiwola, Teslim, Ottomano, Federico, Ozhan, Aleyna Beste, Pagel, Sebastian, Parida, Chiku, Park, Jaehee, Patel, Vraj, Patyukova, Elena, Petersen, Martin Hoffmann, Pinto, Luis, Pizarro, José M., Plessers, Dieter, Pradhan, Tapashree, Pratiush, Utkarsh, Puli, Charishma, Qin, Andrew, Rajabi, Mahyar, Ricci, Francesco, Risch, Elliot, Ríos-García, Martiño, Roy, Aritra, Rug, Tehseen, Sayeed, Hasan M, Scheidgen, Markus, Schilling-Wilhelmi, Mara, Schloz, Marcel, Schöppach, Fabian, Schumann, Julia, Schwaller, Philippe, Schwarting, Marcus, Sharlin, Samiha, Shen, Kevin, Shi, Jiale, Si, Pradip, D'Souza, Jennifer, Sparks, Taylor, Sudhakar, Suraj, Talirz, Leopold, Tang, Dandan, Taran, Olga, Terboven, Carla, Tropin, Mark, Tsymbal, Anastasiia, Ueltzen, Katharina, Unzueta, Pablo Andres, Vasan, Archit, Vinchurkar, Tirtha, Vo, Trung, Vogel, Gabriel, Völker, Christoph, Weinreich, Jan, Yang, Faradawn, Zaki, Mohd, Zhang, Chi, Zhang, Sylvester, Zhang, Weijie, Zhu, Ruijie, Zhu, Shang, Janssen, Jan, Foster, Ian, Blaiszik, Ben

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting in 34 team submissions. The submissions spann

Externí odkaz: http://arxiv.org/abs/2411.15221

Multi-temporal crack segmentation in concrete structure using deep learning approaches

Autor: Harb, Said, Achanccaray, Pedro, Maboudi, Mehdi, Gerke, Markus

Cracks are among the earliest indicators of deterioration in concrete structures. Early automatic detection of these cracks can significantly extend the lifespan of critical infrastructures, such as bridges, buildings, and tunnels, while simultaneous

Externí odkaz: http://arxiv.org/abs/2411.04620

Spectrum and location of ongoing extreme particle acceleration in Cassiopeia A

Autor: Woo, Jooyun, Mori, Kaya, Hailey, Charles J., Spira-Savett, Elizabeth, Bamba, Aya, Grefenstette, Brian W., Humensky, Thomas B., Mukherjee, Reshmi, Safi-Harb, Samar, Temim, Tea, Tsuji, Naomi

Young supernova remnants (SNRs) are believed to be the origin of energetic cosmic rays (CRs) below the "knee" of their spectrum at $\sim3$ petaelectronvolt (PeV, $10^{15}$ eV). Nevertheless, the precise location, duration, and operation of CR acceler

Externí odkaz: http://arxiv.org/abs/2410.16522

Enhancing Source Code Security with LLMs: Demystifying The Challenges and Generating Reliable Repairs

Autor: Islam, Nafis Tanveer, Khoury, Joseph, Seong, Andrew, Bou-Harb, Elias, Najafirad, Peyman

With the recent unprecedented advancements in Artificial Intelligence (AI) computing, progress in Large Language Models (LLMs) is accelerating rapidly, presenting challenges in establishing clear guidelines, particularly in the field of security. Tha

Externí odkaz: http://arxiv.org/abs/2409.00571

Non-Invasive Readout of the Kinetic Inductance of Superconducting Nanostructures

Autor: Nulens, Lukas, Chaves, Davi A. D., Harb, Omar J. Y., Scheerder, Jeroen E., Lejeune, Nicolas, Brahim, Kamal, Raes, Bart, Silhanek, Alejandro V., Van Bael, Margriet J., Van de Vondel, Joris

The energy landscape of multiply connected superconducting structures is ruled by fluxoid quantization due to the implied single-valuedness of the complex wave function. The transitions and interaction between these energy states, each defined by a s

Externí odkaz: http://arxiv.org/abs/2405.11882