Copertina

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

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	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, de Jong, Wibe A., 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, Sheng-Lun, Liao, 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, Li, Calvin, Foster, Ian, Blaiszik, Ben
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Materials Science Chemical Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

_version_	1866915088858873856
author	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 de Jong, Wibe A. 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 Sheng-Lun Liao 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 Li, Calvin Foster, Ian Blaiszik, Ben
author_facet	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 de Jong, Wibe A. 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 Sheng-Lun Liao 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 Li, Calvin Foster, Ian Blaiszik, Ben
contents	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 spanned seven key application areas and demonstrated the diverse utility of LLMs for applications in (1) molecular and material property prediction; (2) molecular and material design; (3) automation and novel interfaces; (4) scientific communication and education; (5) research data management and automation; (6) hypothesis generation and evaluation; and (7) knowledge extraction and reasoning from scientific literature. Each team submission is presented in a summary table with links to the code and as brief papers in the appendix. Beyond team results, we discuss the hackathon event and its hybrid format, which included physical hubs in Toronto, Montreal, San Francisco, Berlin, Lausanne, and Tokyo, alongside a global online hub to enable local and virtual collaboration. Overall, the event highlighted significant improvements in LLM capabilities since the previous year's hackathon, suggesting continued expansion of LLMs for applications in materials science and chemistry research. These outcomes demonstrate the dual utility of LLMs as both multipurpose models for diverse machine learning tasks and platforms for rapid prototyping custom applications in scientific research.
format	Preprint
id	arxiv_https___arxiv_org_abs_2411_15221
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry 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 de Jong, Wibe A. 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 Sheng-Lun Liao 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 Li, Calvin Foster, Ian Blaiszik, Ben Machine Learning Materials Science Chemical Physics 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 spanned seven key application areas and demonstrated the diverse utility of LLMs for applications in (1) molecular and material property prediction; (2) molecular and material design; (3) automation and novel interfaces; (4) scientific communication and education; (5) research data management and automation; (6) hypothesis generation and evaluation; and (7) knowledge extraction and reasoning from scientific literature. Each team submission is presented in a summary table with links to the code and as brief papers in the appendix. Beyond team results, we discuss the hackathon event and its hybrid format, which included physical hubs in Toronto, Montreal, San Francisco, Berlin, Lausanne, and Tokyo, alongside a global online hub to enable local and virtual collaboration. Overall, the event highlighted significant improvements in LLM capabilities since the previous year's hackathon, suggesting continued expansion of LLMs for applications in materials science and chemistry research. These outcomes demonstrate the dual utility of LLMs as both multipurpose models for diverse machine learning tasks and platforms for rapid prototyping custom applications in scientific research.
title	Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
topic	Machine Learning Materials Science Chemical Physics
url	https://arxiv.org/abs/2411.15221