A collaboration between the University of Maryland and the University of California Berkeley
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QANTA Project
QANTA Project
The QANTA project at the University of Maryland uses trivia competitions to compare computer systems against each other and expert humans in games of question answering. The aim is to improve question answering: helping computers better answer questions from learning how trivia experts answer questions, helping understand how to explain question answering in human-computer teams, and helping humans author challenging, interesting questions efficiently. Led by professor Dr. Jordan Boyd-Graber, a team of graduate and undergraduate students from computer science, language science, and information science builds interfaces, algorithms, and datasets to improve human and computer question answering.
We'd love for you to join us in our 2025 competition! See videos of our previous events against top trivia champs, or read about our system:
QANTA Dataset
QANTA Dataset
With the cooperation of the quiz bowl community, we compile datasets of questions that can challenge question answering systems. Read our preprint describing the main dataset. If you're a computer science researcher, this is likely what you came here for!
Human vs. Machine Competitions: Try it!
Human vs. Machine Competitions: Try it!
Read our preprint about the first round of the competition!
Contact Jordan Boyd-Graber or qanta@googlegroups.com for questions / concerns about QANTA.
Contact Irene Ying for questions / concerns about this website.
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