Center for Intelligent Information Retrieval (CIIR) doctoral student Helia Hashemi is the primary developer of ANTIQUE (“Answering Non-facToId QUEstions), a large-scale non-factoid question answering collection that Google AI researchers chose for use in their TF-Ranking (TensorFlow) Tutorial presented during SIGIR 2019 and ICTIR 2019. She, along with co-authors, CIIR Director Bruce Croft, CIIR doctoral student Hamed Zamani, and then-CIIR visiting research scholar Mohammad Aliannejadi of the University of Lugano, released a technical paper, “ANTIQUE: A Non-Factoid Question Answering Benchmark,” to provide details on the collection and to report on benchmark results for a set of retrieval models. More on the project and links to download the CIIR ANTIQUE dataset and the Google hands-on demonstration of TF-Ranking.