11 citations · 20 across the 6 of their papers we have counts for
10 papers
Safeguarding Crowdsourcing Surveys from ChatGPT with Prompt Injection
Chaofan Wang, Samuel Kernan Freire, Mo Zhang +7
ChatGPT and other large language models (LLMs) have proven useful in crowdsourcing tasks, where they can effectively annotate machine learning training data. However, this means th…
Active Hybrid Classification
Evgeny Krivosheev, Fabio Casati, Alessandro Bozzon
Hybrid crowd-machine classifiers can achieve superior performance by combining the cost-effectiveness of automatic classification with the accuracy of human judgment. This paper sh…
Active Learning from Crowd in Document Screening
Evgeny Krivosheev, Burcu Sayin, Alessandro Bozzon +1
In this paper, we explore how to efficiently combine crowdsourcing and machine intelligence for the problem of document screening, where we need to screen documents with a set of m…
Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics
Tim Draws, Nava Tintarev, Ujwal Gadiraju +2
The way pages are ranked in search results influences whether the users of search engines are exposed to more homogeneous, or rather to more diverse viewpoints. However, this viewp…
Designing Evaluations of Machine Learning Models for Subjective Inference: The Case of Sentence Toxicity
Agathe Balayn, Alessandro Bozzon
Machine Learning (ML) is increasingly applied in real-life scenarios, raising concerns about bias in automatic decision making. We focus on bias as a notion of opinion exclusion, t…
Unfairness towards subjective opinions in Machine Learning
Agathe Balayn, Alessandro Bozzon, Zoltan Szlavik
Despite the high interest for Machine Learning (ML) in academia and industry, many issues related to the application of ML to real-life problems are yet to be addressed. Here we pu…