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cs.CL2026
Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory
Runxi Cheng, Yuchen Guan, Yongxian Wei +7
Scaling conditional memory offers a promising way to increase language-model capacity, but existing methods such as Engram learn large memory tables from scratch during pre-trainin…
cs.CL2026
Spectral Characterization and Mitigation of Sequential Knowledge Editing Collapse
Chi Zhang, Mengqi Zhang, Xiaotian Ye +5
Sequential knowledge editing in large language models often causes catastrophic collapse of the model's general abilities, especially for parameter-modifying methods. Existing appr…