{"url":"/task/vertical-federated-learning","name":"Vertical Federated Learning","slug":"vertical-federated-learning","description_markdown":null,"categories":[{"name":"Adversarial","url":"/area/adversarial"},{"name":"Methodology","url":"/area/methodology"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":195,"papers_with_code":46,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":1},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[{"url":"/task/federated-learning","name":"Federated Learning"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":46,"tagged_in_all":195,"items":[{"url":"/paper/fedlearn-algo-a-flexible-open-source-privacy","title":"Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform","date":"2021-07-08","arxiv_id":"2107.04129","repositories_listed":3,"syntology":null},{"url":"/paper/label-inference-attacks-against-vertical","title":"Label Inference Attacks Against Vertical Federated Learning","date":"2022-10-10","arxiv_id":null,"repositories_listed":2,"syntology":null},{"url":"/paper/differentially-private-vertical-federated","title":"Differentially Private Vertical Federated Clustering","date":"2022-08-02","arxiv_id":"2208.01700","repositories_listed":2,"syntology":null},{"url":"/paper/reliable-vertical-federated-learning-in-5g","title":"Reliable Vertical Federated Learning in 5G Core Network Architecture","date":"2025-05-21","arxiv_id":"2505.15244","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/forgetting-any-data-at-any-time-a","title":"Forgetting Any Data at Any Time: A Theoretically Certified Unlearning Framework for Vertical Federated Learning","date":"2025-02-24","arxiv_id":"2502.17081","repositories_listed":1,"syntology":null},{"url":"/paper/unitrans-a-unified-vertical-federated","title":"UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration","date":"2025-01-20","arxiv_id":"2501.11388","repositories_listed":1,"syntology":null},{"url":"/paper/label-privacy-in-split-learning-for-large","title":"Label Privacy in Split Learning for Large Models with Parameter-Efficient Training","date":"2024-12-21","arxiv_id":"2412.16669","repositories_listed":1,"syntology":null},{"url":"/paper/just-a-simple-transformation-is-enough-for","title":"Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning","date":"2024-12-16","arxiv_id":"2412.11689","repositories_listed":1,"syntology":null},{"url":"/paper/vertical-federated-unlearning-via-backdoor","title":"Vertical Federated Unlearning via Backdoor Certification","date":"2024-12-16","arxiv_id":"2412.11476","repositories_listed":1,"syntology":null},{"url":"/paper/query-efficient-adversarial-attack-against","title":"Query-Efficient Adversarial Attack Against Vertical Federated Graph Learning","date":"2024-11-05","arxiv_id":"2411.02809","repositories_listed":1,"syntology":null},{"url":"/paper/vertical-federated-learning-with-missing","title":"Vertical Federated Learning with Missing Features During Training and Inference","date":"2024-10-29","arxiv_id":"2410.22564","repositories_listed":1,"syntology":{"n":14,"n_ran":2,"n_unverified":12,"n_pointer_only":0}},{"url":"/paper/federated-transformer-multi-party-vertical","title":"Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data","date":"2024-10-23","arxiv_id":"2410.17986","repositories_listed":1,"syntology":{"n":3,"n_ran":0,"n_unverified":3,"n_pointer_only":0}},{"url":"/paper/vflip-a-backdoor-defense-for-vertical","title":"VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification","date":"2024-08-28","arxiv_id":"2408.15591","repositories_listed":1,"syntology":null},{"url":"/paper/constructing-adversarial-examples-for","title":"Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit","date":"2024-08-08","arxiv_id":"2408.04310","repositories_listed":1,"syntology":null},{"url":"/paper/a-differentially-private-blockchain-based","title":"A Differentially Private Blockchain-Based Approach for Vertical Federated Learning","date":"2024-07-09","arxiv_id":"2407.07054","repositories_listed":1,"syntology":null},{"url":"/paper/communication-efficient-vertical-federated-1","title":"Communication-efficient Vertical Federated Learning via Compressed Error Feedback","date":"2024-06-20","arxiv_id":"2406.14420","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/share-your-secrets-for-privacy-confidential","title":"Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning","date":"2024-05-31","arxiv_id":"2405.20761","repositories_listed":1,"syntology":null},{"url":"/paper/vertical-federated-learning-for-effectiveness","title":"Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey","date":"2024-05-25","arxiv_id":"2405.17495","repositories_listed":1,"syntology":null},{"url":"/paper/constructing-adversarial-examples-for-1","title":"Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit","date":"2024-05-07","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/a-survey-on-contribution-evaluation-in","title":"A Survey on Contribution Evaluation in Vertical Federated Learning","date":"2024-05-03","arxiv_id":"2405.02364","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-label-information-for-stealthy","title":"URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning","date":"2024-04-30","arxiv_id":"2404.19582","repositories_listed":1,"syntology":null},{"url":"/paper/vflgan-vertical-federated-learning-based","title":"VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication","date":"2024-04-15","arxiv_id":"2404.09722","repositories_listed":1,"syntology":null},{"url":"/paper/vflair-a-research-library-and-benchmark-for","title":"VFLAIR: A Research Library and Benchmark for Vertical Federated Learning","date":"2023-10-15","arxiv_id":"2310.09827","repositories_listed":1,"syntology":null},{"url":"/paper/flexible-differentially-private-vertical","title":"Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings","date":"2023-07-26","arxiv_id":"2308.02362","repositories_listed":1,"syntology":null},{"url":"/paper/vertibench-advancing-feature-distribution","title":"VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks","date":"2023-07-05","arxiv_id":"2307.02040","repositories_listed":1,"syntology":null},{"url":"/paper/glasu-a-communication-efficient-algorithm-for","title":"GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data","date":"2023-03-16","arxiv_id":"2303.09531","repositories_listed":1,"syntology":null},{"url":"/paper/label-inference-attack-against-split-learning","title":"Label Inference Attack against Split Learning under Regression Setting","date":"2023-01-18","arxiv_id":"2301.07284","repositories_listed":1,"syntology":null},{"url":"/paper/coresets-for-vertical-federated-learning","title":"Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering","date":"2022-10-26","arxiv_id":"2210.14664","repositories_listed":1,"syntology":null},{"url":"/paper/efficient-vertical-federated-learning-method","title":"Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples via Least-Squares Solution","date":"2022-10-26","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/feature-reconstruction-attacks-and","title":"Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning","date":"2022-10-13","arxiv_id":"2210.06771","repositories_listed":1,"syntology":null}],"syntology_records":4,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}