Mixhead: Breaking the low-rank bottleneck in multi-head attention language models

Research article (Knowledge-Based Systems, 2022) · cited 17× · AI/ML
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Mixhead: Breaking the low-rank bottleneck in multi-head attention language models

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Mixhead: Breaking the low-rank bottleneck in multi-head attention language models is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Mixhead: Breaking the low-rank bottleneck in multi-head attention language models. Retrieved May 24, 2026, from https://4ort.xyz/entity/mixhead-breaking-the-low-rank-bottleneck-in-multi-head-attention-language-models
MLA “Mixhead: Breaking the low-rank bottleneck in multi-head attention language models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/mixhead-breaking-the-low-rank-bottleneck-in-multi-head-attention-language-models.
BibTeX @misc{4ortxyz_mixhead-breaking-the-low-rank-bottleneck-in-multi-head-attention-language-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Mixhead: Breaking the low-rank bottleneck in multi-head attention language models}}, year = {2026}, url = {https://4ort.xyz/entity/mixhead-breaking-the-low-rank-bottleneck-in-multi-head-attention-language-models}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Mixhead: Breaking the low-rank bottleneck in multi-head attention language models — https://4ort.xyz/entity/mixhead-breaking-the-low-rank-bottleneck-in-multi-head-attention-language-models (retrieved 2026-05-24)

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