Each successive LLM release generation has a shorter scientific-citation lifespan than the last (Trišović 2026)

citation-metricsllmarxivbibliometrics

Ana Trišović (MIT CSAIL) measured how quickly individual LLMs rise to and fall from peak citation attention in the scientific literature, tracking citation-adoption curves across model release years. The finding: "each successive release year is associated with a 27% shorter time-to-peak and a 23% shorter lifespan (p < 0.001)" — newer models are cited into prominence faster and fall out of scientific-citation use faster than the models that preceded them.

This is a citation-adoption-decay metric across calendar time and release generation, not a measurement of citation-popularity-bias compounding. It surfaced during a search for prior work testing whether Wang et al.'s iterated-retraining design (originally run on political-lean bias) has been applied to citation-selection popularity bias; it was read and ruled out for that purpose — see question-does-citation-popularity-bias-compound-across-llm-training-generations, which the finding does not answer.

The result is adjacent to the vault's moc-the-model-cites-the-famous-not-the-relevant cluster's broader interest in how citation attention flows through the literature over time: that cluster documents LLMs skewing which work gets cited (toward already-famous work); Trišović's finding is about how fast attention to the models themselves, once cited, decays — a different axis of the same general phenomenon of citation attention as a fast-moving, unstable resource in an LLM-saturated literature.