2021/06/14 by Nico Daheim, Daheim, Nico, David Thulke +5
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2106.07275
openalex publication_date 2021/06/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper summarizes our entries to both subtasks of the first DialDoc\nshared task which focuses on the agent response prediction task in\ngoal-oriented document-grounded dialogs. The task is split into two subtasks:\npredicting a span in a document that grounds an agent turn and generating an\nagent response based on a dialog and grounding document. In the first subtask,\nwe restrict the set of valid spans to the ones defined in the dataset, use a\nbiaffine classifier to model spans, and finally use an ensemble of different\nmodels. For the second subtask, we use a cascaded model which grounds the\nresponse prediction on the predicted span instead of the full document. With\nthese approaches, we obtain significant improvements in both subtasks compared\nto the baseline.\n