March 11, 2024, 4:47 a.m. | Juhao Liang, Ziwei Wang, Zhuoheng Ma, Jianquan Li, Zhiyi Zhang, Xiangbo Wu, Benyou Wang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.04790v1 Announce Type: new
Abstract: Large Language Models(LLMs) have dramatically revolutionized the field of Natural Language Processing(NLP), offering remarkable capabilities that have garnered widespread usage. However, existing interaction paradigms between LLMs and users are constrained by either inflexibility, limitations in customization, or a lack of persistent learning. This inflexibility is particularly evident as users, especially those without programming skills, have restricted avenues to enhance or personalize the model. Existing frameworks further complicate the model training and deployment process due to …

abstract arxiv capabilities cs.ai cs.cl customization however language language models language processing large language large language models learn limitations llms natural natural language natural language processing nlp online training processing training type usage

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