% generated by tables/make_tables.py from ./results/bibliometrics/cagr_by_category.csv
\begin{table}[htbp]\centering\caption{Volume, compound annual growth and corpus share of the nine AI categories, baseline (2018--2022) and post (2023--2025) periods.}\label{tab:ai_growth}
\begin{threeparttable}\small
\begin{tabular}{lrrrrrrrrr}
\toprule
\textbf{Category} & \textbf{2018} & \textbf{2022} & \textbf{2023} & \textbf{2025} & \textbf{CAGR 18--22} & \textbf{CAGR 23--25} & \textbf{Share 2018} & \textbf{Share 2022} & \textbf{Share 2025} \\
\midrule
LLM & 545 & 1{,}088 & 5{,}194 & 22{,}579 & 0.189 & 1.085 & 0.32 & 0.43 & 5.26 \\
Foundation & 23 & 175 & 285 & 927 & 0.661 & 0.802 & 0.01 & 0.07 & 0.22 \\
Multimodal & 156 & 639 & 966 & 3{,}374 & 0.421 & 0.869 & 0.09 & 0.25 & 0.79 \\
Generative & 255 & 1{,}080 & 1{,}823 & 6{,}371 & 0.434 & 0.870 & 0.15 & 0.42 & 1.48 \\
Agents & 2{,}718 & 2{,}260 & 2{,}495 & 4{,}409 & -0.045 & 0.329 & 1.60 & 0.89 & 1.03 \\
RL & 1{,}648 & 3{,}508 & 4{,}211 & 6{,}605 & 0.208 & 0.252 & 0.97 & 1.38 & 1.54 \\
ML theory & 4{,}511 & 10{,}065 & 11{,}446 & 16{,}399 & 0.222 & 0.197 & 2.66 & 3.95 & 3.82 \\
DL arch. & 3{,}997 & 7{,}423 & 12{,}803 & 17{,}070 & 0.167 & 0.155 & 2.36 & 2.91 & 3.97 \\
AI safety & 526 & 1{,}477 & 2{,}007 & 5{,}442 & 0.294 & 0.647 & 0.31 & 0.58 & 1.27 \\
\bottomrule
\end{tabular}
\begin{tablenotes}\footnotesize\item Counts and shares as stored in the source file (works whose primary category is the row category; shares in per cent of all eligible works of the year). CAGR as in Part IV, eq.~\ref{eq:cagr}; the post-period CAGR uses the 2023 and 2025 end points. Category abbreviations: LLM = large language models; Foundation = foundation models; Generative = generative AI; Agents = AI agents; RL = reinforcement learning; DL arch. = deep-learning architectures; AI safety = AI safety and alignment.\end{tablenotes}
\end{threeparttable}\end{table}