NLLG Quarterly arXiv Report 09/23: What are the most influential current
  AI Papers?
Ran Zhang Aida Kostikova Christoph Leiter Jonas Belouadi Daniil Larionov Yanran Chen Vivian Fresen Steffen Eger
Artificial Intelligence (AI) has witnessed rapid growth, especially in the
subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer
Vision (CV). Keeping pace with this rapid progress poses a considerable
challenge for researchers and professionals in the field. In this arXiv report,
the second of its kind, which covers the period from January to September 2023,
we aim to provide insights and analysis that help navigate these dynamic areas
of AI. We accomplish this by 1) identifying the top-40 most cited papers from
arXiv in the given period, comparing the current top-40 papers to the previous
report, which covered the period January to June; 2) analyzing dataset
characteristics and keyword popularity; 3) examining the global sectoral
distribution of institutions to reveal differences in engagement across
geographical areas. Our findings highlight the continued dominance of NLP:
while only 16% of all submitted papers have NLP as primary category (more than
25% have CV and ML as primary category), 50% of the most cited papers have NLP
as primary category, 90% of which target LLMs. Additionally, we show that i)
the US dominates among both top-40 and top-9k papers, followed by China; ii)
Europe clearly lags behind and is hardly represented in the top-40 most cited
papers; iii) US industry is largely overrepresented in the top-40 most
influential papers.