AI RESEARCH
Hyperloop Transformers
arXiv CS.LG
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ArXi:2604.21254v1 Announce Type: new LLM architecture research generally aims to maximize model quality subject to fixed compute/latency budgets. However, many applications of interest such as edge and on-device deployment are further constrained by the model's memory footprint, thus motivating parameter-efficient architectures for language modeling. This paper describes a simple architecture that improves the parameter-efficiency of LLMs.