% generated by tables/make_tables.py from /Users/simon-pierreboucher/Desktop/UQO/Recherche/Recherche-UQO/informatique/wp44/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}{lrrrrrrr}
\toprule
\textbf{Category} & \textbf{2018} & \textbf{2022} & \textbf{2025} & \textbf{CAGR 18--22} & \textbf{CAGR 23--25} & \textbf{Share 2018} & \textbf{Share 2025} \\
\midrule
LLM & 1{,}635 & 3{,}266 & 45{,}158 & 0.189 & 1.085 & 0.33 & 5.06 \\
Foundation & 46 & 350 & 1{,}854 & 0.661 & 0.802 & 0.01 & 0.21 \\
Multimodal & 470 & 1{,}278 & 6{,}749 & 0.284 & 0.869 & 0.09 & 0.76 \\
Generative & 766 & 2{,}160 & 12{,}743 & 0.296 & 0.870 & 0.15 & 1.43 \\
Agents & 5{,}436 & 4{,}521 & 8{,}819 & -0.045 & 0.329 & 1.09 & 0.99 \\
RL & 3{,}296 & 7{,}017 & 13{,}210 & 0.208 & 0.252 & 0.66 & 1.48 \\
ML theory & 13{,}534 & 20{,}131 & 32{,}798 & 0.104 & 0.197 & 2.71 & 3.67 \\
DL arch. & 11{,}992 & 22{,}270 & 34{,}141 & 0.167 & 0.155 & 2.40 & 3.82 \\
AI safety & 1{,}052 & 2{,}954 & 10{,}885 & 0.294 & 0.647 & 0.21 & 1.22 \\
\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}