[PDF][PDF] Black-Box Data Poisoning Attacks on Crowdsourcing.

P Chen, Y Yang, D Yang, H Sun, Z Chen, P Lin - IJCAI, 2023‏ - ijcai.org
Understanding the vulnerability of label aggregation against data poisoning attacks is key to
ensuring data quality in crowdsourced label collection. State-of-the-art attack mechanisms …

Robust Decision Aggregation with Adversarial Experts

Y Guo, Y Kong - arxiv preprint arxiv:2403.08222, 2024‏ - arxiv.org
We consider a binary decision aggregation problem in the presence of both truthful and
adversarial experts. The truthful experts will report their private signals truthfully with proper …

Do datapoints argue?: Argumentation for hierarchical agreement in datasets

A Bahuguna, S Haydar, A Brännström… - European Conference on …, 2023‏ - Springer
This work aims to utilize quantitative bipolar argumentation to detect deception in machine
learning models. We explore the concept of deception in the context of interactions of a party …

Classifying Workers for Mitigating Adversarial Attacks in Crowdsourcing

ARK First, GPS Second - 2023‏ - researchsquare.com
Crowdsourcing is adopted as a fast and cost-effective system for human computation and
acquiring data for training models in machine learning. Although crowdsourcing has broad …