CPII system ranks FIRST in BOTH SEEN and UNSEEN Tests in the 2022 DialDoc Workshop organized by The Association for Computational Linguistics (ACL)

This challenge provides the necessary data to contestants for free. The data include several thousand passages from US sources from over 480 US government webpages, such as the Department of Motor Vehicles, Veteran Affairs (va.gov), Social Security Administration (ssa.gov), Student Aid (studentaid.gov), etc. The contestants need to generate natural responses to answer questions that are likely asked by the general public seeking related information. The 2022 Shared Task, MultiDoc2Dial, is a new task with a dataset on modeling goal-oriented in multiple documents. The aim is to address more realistic scenarios where a goal-oriented information-seeking conversation involves multiple topics and hence is grounded on different documents. Prof Meng’s team developed a dialog system and competed in the Shared Task. The evaluation includes both the SEEN test and UNSEEN test, depending on whether some of the test data may have been included (by the organizers) in the training data. Out of over 500 submissions from around the world, automatic evaluation shows that Prof Meng’s system ranks FIRST in BOTH SEEN and UNSEEN Tests.