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Experimental Transformer Architecture Merges Attention and MLP Processing

By PulseAugur Editorial · [1 sources] ·

A researcher has developed an experimental Transformer architecture called Gated Attention Projection (GAP). This new design merges attention and MLP processing into a single gated block, deviating from the standard Transformer's separate sublayers. While GAP20 used 19.91% fewer parameters than a standard Transformer and showed a 19.9% improvement in training throughput with torch.compile, the standard Transformer ultimately performed better in final language model accuracy. AI

IMPACT Presents an alternative architectural approach for Transformers that could lead to more efficient models.

RANK_REASON Research paper detailing an experimental architecture. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/MachineLearning →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Experimental Transformer Architecture Merges Attention and MLP Processing

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Research paper detailing an experimental architecture. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/WAMFT ·

    I merged attention and MLP processing into a single gated Transformer block. GAP [R]

    <!-- SC_OFF --><div class="md"><p>Hi everyone!</p> <p>I've been experimenting with an alternative Transformer architecture called <strong>GAP (Gated Attention Projection)</strong>.</p> <p>The main idea is to combine attention and MLP-style processing into a single gated block, in…

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