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cs.LG2025
Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation
Quan Xiao, Yutong Xuan, Gaowen Liu +2
Supervised fine-tuning (SFT) datasets are critical to the downstream performance of large language models, yet they often contain low-quality or harmful question-response pairs. To…
cs.LG2025
FedHFT: Efficient Federated Finetuning with Heterogeneous Edge Clients
Fatih Ilhan, Selim Furkan Tekin, Tiansheng Huang +6
Fine-tuning pre-trained large language models (LLMs) has become a common practice for personalized natural language understanding (NLU) applications on downstream tasks and domain-…
cs.LG2025
A First-order Generative Bilevel Optimization Framework for Diffusion Models
Quan Xiao, Hui Yuan, A F M Saif +4
Diffusion models, which iteratively denoise data samples to synthesize high-quality outputs, have achieved empirical success across domains. However, optimizing these models for do…