2 papers
cs.AI2026
FedLAFP: Low-Rank Aggregation Meets Full-Rank Personalization in Federated Fine-Tuning
Mengjun Yi, Huaian Gu, Yinghao Ai +2
Federated parameter-efficient fine-tuning enables clients to adapt pre-trained models without sharing raw data or communicating the full model, but statistical heterogeneity makes…
cs.LG2026
Trajectory Learnability for Offline On-Policy Distillation with Imperfect Teachers
Yihao Ai, Beibei Lin, Weilong Yan +1
Offline on-policy distillation gains efficiency by collecting student trajectories and teacher supervision once and reusing them throughout optimization. The same reuse makes imper…