| Title: |
INDUS: Effective and Efficient Language Models for Scientific Applications |
| Authors: |
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, Michael M.; Fancher, Elizabeth; Gerasimov, Irina; Mehrabian, Armin; Sanders, Lauren; Costes, Sylvain V.; Blanco-Cuaresma, Sergi; Lockhart, Kelly; Allen, Thomas; Grezes, Felix; Ansdell, Megan; Accomazzi, Alberto; El-Kurdi, Yousef; Wertheimer, Davis; Pfitzmann, Birgit; Berrospi Ramis, Cesar; Dolfi, Michele; De Lima, Rafael Teixeira; Vagenas, Panagiotis; Mukkavilli, S. Karthik; Staar, Peter W. J.; Vahidinia, Sanaz; McGranaghan, Ryan; Lee, Tsengdar J. |
| Source: |
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track ; page 98-112 |
| Publisher Information: |
Association for Computational Linguistics |
| Publication Year: |
2024 |
| Document Type: |
conference object |
| Language: |
unknown |
| DOI: |
10.18653/v1/2024.emnlp-industry.9 |
| Availability: |
https://doi.org/10.18653/v1/2024.emnlp-industry.9 |
| Accession Number: |
edsbas.CD8D055F |
| Database: |
BASE |