AAAI2026-Reproducibility Checklist代码

放在\bibliography{AnonymousSubmission/LaTeX/aaai2026}后面即可

定义一个新的命令放在文件开头：
\newcommand{\highlight}[1]{\textbf{\underline{#1}}}

% Reproducibility Checklist
\section{Reproducibility Checklist}

\begin{enumerate}
    \item This paper:
    \begin{itemize}
        \item Includes a conceptual outline and/or pseudocode description of AI methods introduced (\textbf{\underline{yes}}/partial/no/NA)
        \item Clearly delineates statements that are opinions, hypotheses, and speculation from objective facts and results (\highlight{yes}/no)
        \item Provides well-marked pedagogical references for less-familiar readers to gain background necessary to replicate the paper (\highlight{yes}/no)
    \end{itemize}

    \item Does this paper make theoretical contributions? (\highlight{yes}/no) \\
    If yes, please complete the list below:
    \begin{itemize}
        \item All assumptions and restrictions are stated clearly and formally. (\highlight{yes}/partial/no)
        \item All novel claims are stated formally (e.g., in theorem statements). (\highlight{yes}/partial/no)
        \item Proofs of all novel claims are included. (\highlight{yes}/partial/no)
        \item Proof sketches or intuitions are given for complex and/or novel results. (\highlight{yes}/partial/no)
        \item Appropriate citations to theoretical tools used are given. (\highlight{yes}/partial/no)
        \item All theoretical claims are demonstrated empirically to hold. (\highlight{yes}/partial/no/NA)
        \item All experimental code used to eliminate or disprove claims is included. (\highlight{yes}/no/NA)
    \end{itemize}

    \item Does this paper rely on one or more datasets? (\highlight{yes}/no) \\
    If yes, please complete the list below:
    \begin{itemize}
        \item A motivation is given for why the experiments are conducted on the selected datasets. (\highlight{yes}/partial/no/NA)
        \item All novel datasets introduced in this paper are included in a data appendix. (\highlight{yes}/partial/no/NA)
        \item All novel datasets introduced in this paper will be made publicly available upon publication with a license allowing free research use. (yes/partial/no/\highlight{NA})
        \item All datasets drawn from the existing literature are accompanied by appropriate citations. (\highlight{yes}/no/NA)
        \item All datasets drawn from the existing literature are publicly available. (\highlight{yes}/partial/no/NA)
        \item Datasets that are not publicly available are described in detail, with justification. (yes/partial/no/\highlight{NA})
    \end{itemize}

    \item Does this paper include computational experiments? (yes/no) \\
    If yes, please complete the list below:
    \begin{itemize}
        \item Number/range of values tried per (hyper-)parameter and selection criteria are reported. (yes/partial/no/NA)
        \item Code for data preprocessing is included in the appendix. (yes/partial/no)
        \item Source code for conducting and analyzing experiments is included. (yes/partial/no)
        \item Code will be released publicly upon publication with a permissive license. (yes/partial/no)
        \item Code includes comments with implementation details and paper references. (yes/partial/no)
        \item Seed setting methods for stochastic algorithms are described. (yes/partial/no/NA)
        \item Computing infrastructure (hardware/software specs) is reported. (yes/partial/no)
        \item Evaluation metrics are formally described with motivations. (yes/partial/no)
        \item Number of runs per result is specified. (yes/no)
        \item Performance analysis includes variation, confidence, or distributions. (yes/no)
        \item Significance of performance differences is assessed with statistical tests. (yes/partial/no)
        \item Final (hyper-)parameter settings are listed. (yes/partial/no/NA)
    \end{itemize}
\end{enumerate}

效果就是这样，接在References后面。