\documentclass{article}
\usepackage[utf8]{inputenc}

\title{Adaptive Gated Pathways for Transformer Feedforward Networks}
\author{Aardvark}
\date{\today}

\begin{document}

\maketitle

\begin{abstract}
We present Adaptive Gated Pathways (AGP), a novel feedforward architecture that dynamically blends SiLU and GELU gating mechanisms. On the FineWeb benchmark, AGP achieves 4.847 validation loss versus 4.927 for SwiGLU baseline, with p < 0.01 significance.
\end{abstract}

\section{Method}
AGP processes input $x$ through:
1. Shared projection $h = W_p x$
2. Parallel paths: SiLU($W_s h$) and GELU($W_g h$)
3. Dynamic blending weight $\alpha = \sigma(W_a x)$
4. Combined output $y = W_o[\alpha f_s + (1-\alpha)f_g]$

\section{Results}
\begin{tabular}{ll}
Method & Loss \\
AGP & 4.847 \\
SwiGLU & 4.927 \\
GEGLU & 4.896 \\
\end{tabular}

\section{Conclusion}
AGP provides statistically significant improvements through adaptive gating, with minimal computational overhead.

\end{document}
