Freely Long-Thinking Transformer (FraiLT)

• URL: http://arxiv.org/abs/2401.11626v2
• Date: Sat, 24 Feb 2024 12:11:56 GMT
• Title: Freely Long-Thinking Transformer (FraiLT)
• Authors: Akbay Tabak
• Abstract summary: Freely Long-Thinking Transformer (FraiLT) is an improved transformer model designed to enhance processing capabilities without scaling up size. FraiLT utilizes a recursion approach, iterating over a subset of layers multiple times, and introduces iteration encodings to maintain awareness across these cycles. When evaluated on a synthetic story dataset, FraiLT outperformed larger models, showcasing its ability to deliver high-quality performance while reducing memory demands.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Freely Long-Thinking Transformer (FraiLT) is an improved transformer model designed to enhance processing capabilities without scaling up size. It utilizes a recursive approach, iterating over a subset of layers multiple times, and introduces iteration encodings to maintain awareness across these cycles. Iteration encoding allows FraiLT to achieve the interpretive depth of larger models in a compact form. When evaluated on a synthetic story dataset, FraiLT outperformed larger models, showcasing its ability to deliver high-quality performance while reducing memory demands. This model represents a step forward towards more efficient and accessible language models.

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