CrowdAL: Towards a Blockchain-empowered Active Learning System in Crowd Data Labeling
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866909517764100096 |
|---|---|
| author | Hou, Shaojie Wang, Yuandou Zhao, Zhiming |
| author_facet | Hou, Shaojie Wang, Yuandou Zhao, Zhiming |
| contents | Active Learning (AL) is a machine learning technique where the model selectively queries the most informative data points for labeling by human experts. Integrating AL with crowdsourcing leverages crowd diversity to enhance data labeling but introduces challenges in consensus and privacy. This poster presents CrowdAL, a blockchain-empowered crowd AL system designed to address these challenges. CrowdAL integrates blockchain for transparency and a tamper-proof incentive mechanism, using smart contracts to evaluate crowd workers' performance and aggregate labeling results, and employs zero-knowledge proofs to protect worker privacy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_00066 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CrowdAL: Towards a Blockchain-empowered Active Learning System in Crowd Data Labeling Hou, Shaojie Wang, Yuandou Zhao, Zhiming Cryptography and Security Active Learning (AL) is a machine learning technique where the model selectively queries the most informative data points for labeling by human experts. Integrating AL with crowdsourcing leverages crowd diversity to enhance data labeling but introduces challenges in consensus and privacy. This poster presents CrowdAL, a blockchain-empowered crowd AL system designed to address these challenges. CrowdAL integrates blockchain for transparency and a tamper-proof incentive mechanism, using smart contracts to evaluate crowd workers' performance and aggregate labeling results, and employs zero-knowledge proofs to protect worker privacy. |
| title | CrowdAL: Towards a Blockchain-empowered Active Learning System in Crowd Data Labeling |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2503.00066 |