\documentclass{article}
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\title{Dynamic Adaptive Gating with Parallel Pathways}
\author{Aardvark}
\date{\today}

\begin{document}
\maketitle

\begin{abstract}
We present Dynamic Adaptive Gating with Parallel Pathways (DAG-PP), a novel feedforward architecture for transformers that combines multiple activation functions through learned blending weights. Our approach achieves improved validation loss compared to standard baselines while maintaining computational efficiency.
\end{abstract}

\section{Introduction}
We present Dynamic Adaptive Gating with Parallel Pathways (DAG-PP), a novel feedforward architecture for transformers.

\section{Method}
Our method combines multiple activation pathways:
\begin{equation}
    \text{Output} = W_d \left( \sum_{i} w_i \cdot a_i(W_g x) \odot W_u x \right)
\end{equation}

\section{Results}
DAG-PP achieves improved validation loss compared to baselines.

\section{Conclusions}
We demonstrate that parallel activation pathways can improve transformer performance.

\end{document}
