--- title: "FLsystem-paper" type: "tool" slug: "amberljc-flsystem-paper" canonical_url: "https://www.graphcanon.com/tools/amberljc-flsystem-paper" github_url: "https://github.com/AmberLJC/FLsystem-paper" homepage_url: null stars: 75 forks: 7 primary_language: null license: null archived: false categories: ["model-training", "llm-frameworks", "inference-serving"] tags: ["mlsys", "systems", "machine-learning", "federated-learning", "awesome-list", "papers"] updated_at: "2026-07-11T23:38:54.902634+00:00" --- # FLsystem-paper > Federated Learning Systems Paper List Federated Learning Systems Paper List ## Facts - Repository: https://github.com/AmberLJC/FLsystem-paper - Stars: 75 · Forks: 7 · Open issues: 1 · Watchers: 4 - Last pushed: 2024-02-07T05:08:39+00:00 ## Trust & health _Signals computed from public GitHub metadata. Not a security guarantee._ - Maintenance: Dormant (computed 2026-07-11T23:38:51.352Z) - Security scan: No lockfile (0 critical, 0 high, 0 medium, 0 low) · last scan 2026-07-11T23:38:51.667Z - Full report: [trust report](/tools/amberljc-flsystem-paper/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/amberljc-flsystem-paper/trust) ## Categories - [Model Training](/categories/model-training.md) - [LLM Frameworks](/categories/llm-frameworks.md) - [Inference & Serving](/categories/inference-serving.md) ## Tags mlsys, systems, machine-learning, federated-learning, awesome-list, papers ## Category neighbours (exploratory) _Same-category tools for discovery only - not curated alternatives. Cap shown at six._ - [awesome](/tools/sindresorhus-awesome.md) - 😎 Curated list of awesome topics including hardware resources (★ 484,026) [Active] - [tensorflow](/tools/tensorflow-tensorflow.md) - An Open Source Machine Learning Framework for Everyone (★ 196,300) [Very active] - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT is the vision of accessible AI for everyone, to use and to build on. (★ 185,464) [Very active] - [ollama](/tools/ollama-ollama.md) - Get up and running with various large language models using Ollama. (★ 175,936) [Very active] - [prompts.chat](/tools/f-prompts-chat.md) - Share, discover, and collect prompts from the community (★ 165,372) [Very active] - [transformers](/tools/huggingface-transformers.md) - Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models (★ 162,482) [Very active] _+ 2 more not listed._ ## README (excerpt) _Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._ ```text # Awesome Federated Computation Systems Papers A curated list of **FL system**-related academic papers, articles, tutorials, slides and projects. Star this repository, and then you can keep abreast of the latest developments of this booming research field. Papers with 🎓 have been peer-reviewed and presented in academic conferences. ## Table of Contents - [Awesome Federated Computation Systems Papers](#awesome-federated-computation-systems-papers) - [Table of Contents](#table-of-contents) - [FL Systems from big tech companies](#fl-systems-from-big-tech-companies) - [Paper](#paper) - [Framework](#framework) - [Vertical FL](#vertical-fl) - [Open-source FL Framework](#open-source-fl-framework) - [Edge / Mobile](#edge--mobile) - [Federated Computation Systems](#federated-computation-systems) - [Optimization for FL Systems](#optimization-for-fl-systems) - [Security and Privacy](#security-and-privacy) - [Real-world FL Application](#real-world-fl-application) - [Real-world device traces](#real-world-device-traces) - [Survey](#survey) - [General insight for FL](#general-insight-for-fl) - [Other FL paper list](#other-fl-paper-list) ## FL Systems from big tech companies ### Paper >Cross-device - **Apple**: Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications | [`PDF`](https://arxiv.org/pdf/2102.08503.pdf), [`PDF`](https://docs-assets.developer.apple.com/ml-research/papers/learning-with-privacy-at-scale.pdf) - **Google**: Towards Federated Learning at Scale: System Design | [`MLSys21`](https://arxiv.org/abs/1902.01046), [`Github`](https://www.tensorflow.org/federated)🎓 - **Meta**: Papaya: Practical, Private, and Scalable Federated Learning | [`MLSys22`](https://arxiv.org/abs/2111.04877) 🎓 - **Microsoft**: FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations | [`PDF`](https://arxiv.org/abs/2203.13789), [`Github`](https://github.com/microsoft/msrflute) - **Alibaba-1**: FederatedScope: A Flexible Federated Learning Platform for Heterogeneity| [`PDF`](https://arxiv.org/pdf/2204.05011.pdf) - **Alibaba-2**: FederatedScope: FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning |[`KDD22`](https://arxiv.org/abs/2204.05562) 🎓 > Federated Analytics - **LinkedIn**: LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale | [`PDF`](https://arxiv.org/abs/2002.05839) - **Alibaba-3**: Walle: An End-to-End, General-Purpose, and Large-Scale Production System for Device-Cloud Collaborative Machine Learning | [`PDF`](https://www.usenix.org/system/files/osdi22-lv.pdf), [`Github`](https://github.com/alibaba/MNN) 🎓 >Cross-silo - **IBM**: IBM Federated Learning: An Enterprise Framework White Paper | [`PDF`](https://arxiv.org/pdf/2007.10987.pdf), [`Github`](https://ibmfl.mybluemix.net/github) - **Nvidia**: Federated Learning for Healthcare Using NVIDIA *Clara* | [`PDF`](https://developer.download.nvidia.com/CLARA/Federated-Learning-Training-for-Healthcare-Using-NVIDIA-Clara.pdf), [`Github`](https://github.com/NVIDIA/NVFlare) - **WeBank**: Federated Learning White Paper V1.0 | [`PDF`](​​https://aisp-1251170195.cos.ap-hongkong.myqcloud.com/fedweb/1552917186945.pdf), [`FATE`](https://github.com/FederatedAI/FATE), [`KubeFATE`](https://github.com/FederatedAI/KubeFATE), [FATE-FLOW](https://federatedai.github.io/FATE-Flow/latest/fate_flow/), [FATE-LLM](https://arxiv.org/pdf/2310.10049.pdf) ### Framework - Cisco: Flame | [`Github`](https://github.com/cisco-open/flame) - [Federated Learning Operations Made Simple with Flame](https://arxiv.org/abs/2305.05118) - OpenMined: PySyft | [`Github`](https://github.com/OpenMined/PySyft) - Baidu: Paddle | [`Github`](https://github.com/PaddlePaddle/PaddleFL) - ByteDance: Fedlearner | [`Github`](https://github.com/bytedance/fedlearner) - Meta: FLSim | [`Github`](https://github.com/facebookresearch/FL ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/amberljc-flsystem-paper`](/api/graphcanon/tools/amberljc-flsystem-paper) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_