This line of work deals with statistical methods to aggregate information from many sources in an attempt to discover the underlying ground truth, focusing on complex labels (beyond multiple-choice and real-valued).
- Truth Discovery via Proxy Voting. Reshef Meir, Ofra Amir, Gal Cohensius, Omer Ben-Porat, and Lirong Xia. AAAI’23 [Arxiv] ← start here
- Efficient Online Crowdsourcing with Complex Annotations. Reshef Meir, Viet-An Nguyen, Xu Chen, Jagdish Ramakrishnan and Udi Weinsberg. AAAI 2024. [Arxiv]
- Empirical Bayes approach to Truth Discovery problems. Tsviel Ben-Shabat, Reshef Meir, and David Azriel, UAI ’22. [Arxiv]
- When is Proximity-based Truth Discovery Good Enough? Doron Kabla and Reshef Meir. [Working paper]
- Maximum Likelihood Voting Rules for Heterogeneous Voters. Doron Kabla and Reshef Meir. [Working paper]