Results show that GBDT++ is superior to the fine-tuned language model on the questions under the category matching (68.1% vs. 57.0%) and the latter model is more capable of answering implicit questions (e.g., under the category summary, logic, and commonsense) which require aggregation of information from multiple sentences, the understanding of the entire dialogue, or the utilization of world knowledge.
we further define four subcategories as follows.