Paper: Recent Advances in Generative AI and Large Language Models: Current
Authors: Desta Haileselassie Hagos, Rick Battle, and Danda B. Rawat
Abstract: The emergence of Generative Artificial Intelligence (AI) and Large LanguageModels (LLMs) has marked a new era of Natural Language Processing (NLP),introducing unprecedented capabilities that are revolutionizing variousdomains. This paper explores the current state of these cutting-edgetechnologies, demonstrating their remarkable advancements and wide-rangingapplications. Our paper contributes to providing a holistic perspective on thetechnical foundations, practical applications, and emerging challenges withinthe evolving landscape of Generative AI and LLMs. We believe that understandingthe generative capabilities of AI systems and the specific context of LLMs iscrucial for researchers, practitioners, and policymakers to collaborativelyshape the responsible and ethical integration of these technologies intovarious domains. Furthermore, we identify and address main research gaps,providing valuable insights to guide future research endeavors within the AIresearch community.
Reasoning: produce the is_lm_paper. We start by examining the title and abstract for key terms related to language models. The title mentions "Generative AI and Large Language Models," which directly indicates a focus on language models. The abstract further elaborates on the advancements, applications, and challenges of Large Language Models (LLMs), reinforcing the focus on this specific area of AI. Given these points, it is clear that the paper is centered around language models.
Paper: Recent Advances in Generative AI and Large Language Models: Current
Authors: Desta Haileselassie Hagos, Rick Battle, and Danda B. Rawat
Abstract: The emergence of Generative Artificial Intelligence (AI) and Large LanguageModels (LLMs) has marked a new era of Natural Language Processing (NLP),introducing unprecedented capabilities that are revolutionizing variousdomains. This paper explores the current state of these cutting-edgetechnologies, demonstrating their remarkable advancements and wide-rangingapplications. Our paper contributes to providing a holistic perspective on thetechnical foundations, practical applications, and emerging challenges withinthe evolving landscape of Generative AI and LLMs. We believe that understandingthe generative capabilities of AI systems and the specific context of LLMs iscrucial for researchers, practitioners, and policymakers to collaborativelyshape the responsible and ethical integration of these technologies intovarious domains. Furthermore, we identify and address main research gaps,providing valuable insights to guide future research endeavors within the AIresearch community.
Link: https://arxiv.org/abs/2407.14962
Reasoning: produce the is_lm_paper. We start by examining the title and abstract for key terms related to language models. The title mentions "Generative AI and Large Language Models," which directly indicates a focus on language models. The abstract further elaborates on the advancements, applications, and challenges of Large Language Models (LLMs), reinforcing the focus on this specific area of AI. Given these points, it is clear that the paper is centered around language models.