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Citations are a key ingredient of scientific research to relate a paper toothers published in the community. Recently, it has been noted that there is acitation age bias in the Natural Language Processing (NLP) community, one ofthe currently fastest growing AI subfields, in that the mean age of thebibliography of NLP papers has become ever younger in the last few years,leading to `citation amnesia' in which older knowledge is increasinglyforgotten. In this work, we put such claims into perspective by analyzing thebibliography of $\sim$300k papers across 15 different scientific fieldssubmitted to the popular preprint server Arxiv in the time period from 2013 to2022. We find that all AI subfields (in particular: cs.AI, cs.CL, cs.CV, cs.LG)have similar trends of citation amnesia, in which the age of the bibliographyhas roughly halved in the last 10 years (from above 12 in 2013 to below 7 in2022), on average. Rather than diagnosing this as a citation age bias in theNLP community, we believe this pattern is an artefact of the dynamics of theseresearch fields, in which new knowledge is produced in ever shorter timeintervals.

Is there really a Citation Age Bias in NLP?