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cs.LG2026
Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs
Hanlin Cai, Kai Li, Houtianfu Wang +4
Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated learning, FFT enables distr…
cs.IR2026
Unbiased Rectification for Sequential Recommender Systems Under Fake Orders
Qiyu Qin, Yichen Li, Haozhao Wang +3
Fake orders pose increasing threats to sequential recommender systems by misleading recommendation results through artificially manipulated interactions, including click farming, c…
cs.AI2026
Nonlinearity as Rank: Generative Low-Rank Adapter with Radial Basis Functions
Yihao Ouyang, Shiwei Li, Haozhao Wang +6
Low-rank adaptation (LoRA) approximates the update of a pretrained weight matrix using the product of two low-rank matrices. However, standard LoRA follows an explicit-rank paradig…