Furthermore, we show that instruction tuning with CoT Collection allows LMs to possess stronger few-shot learning capabilities on 4 domain-specific tasks, resulting in an improvement of +2. 24% (Flan-T5 3B) and +2. 37% (Flan-T5 11B), even outperforming ChatGPT utilizing demonstrations until the max length by a +13. 98% margin.
Ranked #1 on Few-Shot Learning on PubMedQA
To improve the correctness of the explanations, fine-tuning language models with explanation data is needed.
In this paper, we propose to leverage the unique characteristics of dialogues sharing commonsense knowledge across participants, to resolve the difficulties in summarizing them.
Ranked #2 on Text Summarization on DialogSum