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[PDF][PDF] Black-Box Data Poisoning Attacks on Crowdsourcing.
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 …
ensuring data quality in crowdsourced label collection. State-of-the-art attack mechanisms …
Robust Decision Aggregation with Adversarial Experts
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 …
adversarial experts. The truthful experts will report their private signals truthfully with proper …
Do datapoints argue?: Argumentation for hierarchical agreement in datasets
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 …
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 …
acquiring data for training models in machine learning. Although crowdsourcing has broad …