FedL Lab – Research & Notes

A compact guide to our papers, presentations, and session notes. This README links to key files in this repository for quick access.

Contents

• Papers
  • LoRA
  • Presentations
  • clustering
• Sessions notes

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Quick access

• LoRA

  • Bian_LoRA-FAIR_Federated_LoRA_Fine-Tuning_with_Aggregation_and_Initialization_Refinement_ICCV_2025_paper.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/Bian_LoRA-FAIR_Federated_LoRA_Fine-Tuning_with_Aggregation_and_Initialization_Refinement_ICCV_2025_paper.pdf
  • CE-LoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/CE-LoRA.pdf
  • FL-TAC.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FL-TAC.pdf
  • FLASC.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FLASC.pdf
  • FLoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FLoRA.pdf
  • FRLoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FRLoRA.pdf
  • FSLoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FSLoRA.pdf
  • FedLEASE.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FedLEASE.pdf
  • FedLFC.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FedLFC.pdf
  • FedLoRU.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FedLoRU.pdf
  • FedSA-LoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FedSA-LoRA.pdf
  • FlexLoRA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/FlexLoRA.pdf
  • ICLR-2025-federated-residual-low-rank-adaption-of-large-language-models-Paper-Conference.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/ICLR-2025-federated-residual-low-rank-adaption-of-large-language-models-Paper-Conference.pdf
  • LoRA-FAIR.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/LoRA-FAIR.pdf
  • links.txt
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/LoRA/links.txt

• Presentations

  • FLORA-Presentation2.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/Presentations/12_18_2025/FLORA-Presentation2.pdf
  • LoRAinFL.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/Presentations/12_6_2025/LoRAinFL.pdf
  • soft_fed_presentation.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/Presentations/12_6_2025/soft_fed_presentation.pdf

• clustering

  • Client-Centric.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/Client-Centric.pdf
  • FedAC.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedAC.pdf
  • FedCluster.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedCluster.pdf
  • FedEff.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedEff.pdf
  • FedSC.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedSC.pdf
  • FedSoft.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedSoft.pdf
  • FedSplit.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/FedSplit.pdf
  • IFCA.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/IFCA.pdf
  • LCFL.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/LCFL.pdf
  • Survey_on_cluster_based_learning.pdf
    • GitHub: https://github.com/ampardra/FedL/tree/main/papers/clustering/Survey_on_cluster_based_learning.pdf

• Sessions notes

  • 12_06_2025.md
    • GitHub: https://github.com/ampardra/FedL/tree/main/sessions_note/12_06_2025.md
  • 12_18_2025.md
    • GitHub: https://github.com/ampardra/FedL/tree/main/sessions_note/12_18_2025.md

Quick start tips

• Keep this updated as you make new files.