A Knowledge-Grounded Dialog System Based on Pre-Trained Language Models (2106.14444v1)

Abstract: We present a knowledge-grounded dialog system developed for the ninth Dialog System Technology Challenge (DSTC9) Track 1 - Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access. We leverage transfer learning with existing LLMs to accomplish the tasks in this challenge track. Specifically, we divided the task into four sub-tasks and fine-tuned several Transformer models on each of the sub-tasks. We made additional changes that yielded gains in both performance and efficiency, including the combination of the model with traditional entity-matching techniques, and the addition of a pointer network to the output layer of the LLM.