GPart: End-to-End Isometric Fine-Tuning via Global Parameter Partitioning
arXiv:2605.14841v2 Announce Type: replace-cross Abstract: Low-rank adaptation (LoRA) has become a dominant paradigm for parameter-efficient fine-tuning (PEFT) of large-scale deep learning models. However, its bilinear parameterization induces a…
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Published4 h ago (Fri, 02 Oct 2026 04:00:00 GMT)
RetrievedFri, 02 Oct 2026 07:00:28 GMT via rss
ClassifiedFri, 02 Oct 2026 07:00:40 GMT by heuristic
AuthorPaolo Mandica, Micha{\l} Brzozowski, Zuzanna Dubanowska, Neo Christopher Chung