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pro vyhledávání: '"Ghosh, Samujjwal"'
Autor:
Gosal, Gurpreet, Xu, Yishi, Ramakrishnan, Gokul, Joshi, Rituraj, Sheinin, Avraham, Zhiming, Chen, Mishra, Biswajit, Vassilieva, Natalia, Hestness, Joel, Sengupta, Neha, Sahu, Sunil Kumar, Jia, Bokang, Pandit, Onkar, Katipomu, Satheesh, Kamboj, Samta, Ghosh, Samujjwal, Pal, Rahul, Mullah, Parvez, Doraiswamy, Soundar, Chami, Mohamed El Karim, Nakov, Preslav
We present an efficient method for adapting a monolingual Large Language Model (LLM) to another language, addressing challenges of catastrophic forgetting and tokenizer limitations. We focus this study on adapting Llama 2 to Arabic. Our two-stage app
Externí odkaz:
http://arxiv.org/abs/2407.12869
Online social media works as a source of various valuable and actionable information during disasters. These information might be available in multiple languages due to the nature of user generated content. An effective system to automatically identi
Externí odkaz:
http://arxiv.org/abs/2203.02912
Contrastive pretraining techniques for text classification has been largely studied in an unsupervised setting. However, oftentimes labeled data from related tasks which share label semantics with current task is available. We hypothesize that using
Externí odkaz:
http://arxiv.org/abs/2112.11389
Identification and categorization of social media posts generated during disasters are crucial to reduce the sufferings of the affected people. However, lack of labeled data is a significant bottleneck in learning an effective categorization system f
Externí odkaz:
http://arxiv.org/abs/2104.01436
Akademický článek
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Publikováno v:
International Journal of Advances in Engineering Sciences & Applied Mathematics; Dec2017, Vol. 9 Issue 4, p224-237, 14p