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cs.LG2026
DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models
Haichao Sha, Zihao Wang, Yuncheng Wu +2
Large language models (LLMs) are commonly adapted to downstream tasks through fine-tuning, but fine-tuning data often contains sensitive information that may be leaked by the resul…
cs.LG2026
Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation
Hong Chen, Pengcheng Wu, Yuanguo Lin +4
We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules, not just static models, to tac…