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Modern Transformers Are Implicit Hybrids: From Functional Differentiation to Principled Hybrid Architecture Design
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hybrid architecturetransformerszero-shot learningpositional encoding
2609.02986
Builder Relevance
1h ago80%
Abstract
This paper proposes a principled hybrid architecture design for Transformers that improves retrieval and zero-shot long-context extrapolation.
Reality Card
Core Claim
The Head-wise Hybrid Architecture (HwH) retains strong language modeling while significantly enhancing retrieval and zero-shot long-context extrapolation compared to existing models.
Method / Result
HwH achieves a FA-to-LA ratio below 1:3, improving performance metrics over Transformer, LA, and a layer-wise hybrid baseline.
Limitations
The taxonomy derived from behavioral probes may not be comprehensive, potentially limiting the reproducibility of findings.
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