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The rapid growth of information in the field of Generative ArtificialIntelligence (AI), particularly in the subfields of Natural Language Processing(NLP) and Machine Learning (ML), presents a significant challenge forresearchers and practitioners to keep pace with the latest developments. Toaddress the problem of information overload, this report by the NaturalLanguage Learning Group at Bielefeld University focuses on identifying the mostpopular papers on arXiv, with a specific emphasis on NLP and ML. The objectiveis to offer a quick guide to the most relevant and widely discussed research,aiding both newcomers and established researchers in staying abreast of currenttrends. In particular, we compile a list of the 40 most popular papers based onnormalized citation counts from the first half of 2023. We observe thedominance of papers related to Large Language Models (LLMs) and specificallyChatGPT during the first half of 2023, with the latter showing signs ofdeclining popularity more recently, however. Further, NLP related papers arethe most influential (around 60\% of top papers) even though there are twice asmany ML related papers in our data. Core issues investigated in the mostheavily cited papers are: LLM efficiency, evaluation techniques, ethicalconsiderations, embodied agents, and problem-solving with LLMs. Additionally,we examine the characteristics of top papers in comparison to others outsidethe top-40 list (noticing the top paper's focus on LLM related issues andhigher number of co-authors) and analyze the citation distributions in ourdataset, among others.

NLLG Quarterly arXiv Report 06/23: What are the most influential current AI Papers?