OFL-W3: A One-shot Federated Learning System on Web 3.0
Summary: OFL-W3: a cost-aware one-shot federated learning system for Web3 that minimizes on-chain storage/compute using IPFS and lightweight smart contracts while formalizing model buyer/owner roles with token incentives. Integrates PFNM aggregation, a leave-one-out incentive example and a Flask backend to demonstrate feasibility of single-round FL under blockchain transaction and gas constraints. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Linshan Jiang
- 2. Moming Duan
- 3. Bingsheng He
- 4. Yulin Sun
- 5. Peishen Yan
- 6. Yang Hua
- 7. Tao Song
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,716 | Federated and Balanced Clustering for High-dimensional Data | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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