2 code implementations • 7 Jun 2023 • Zixian Huang, Jiaying Zhou, Gengyang Xiao, Gong Cheng
Previous researches found that in-context learning is an effective approach to exploiting LLM, by using a few task-related labeled data as demonstration examples to construct a few-shot prompt for answering new questions.
1 code implementation • NAACL 2022 • Zixian Huang, Ao Wu, Jiaying Zhou, Yu Gu, Yue Zhao, Gong Cheng
A trending paradigm for multiple-choice question answering (MCQA) is using a text-to-text framework.
Ranked #10 on Question Answering on OpenBookQA
1 code implementation • Findings (EMNLP) 2021 • Zixian Huang, Ao Wu, Yulin Shen, Gong Cheng, Yuzhong Qu
Scenario-based question answering (SQA) requires retrieving and reading paragraphs from a large corpus to answer a question which is contextualized by a long scenario description.
1 code implementation • 1 May 2020 • Shuxin Li, Zixian Huang, Gong Cheng, Evgeny Kharlamov, Kalpa Gunaratna
A prominent application of knowledge graph (KG) is document enrichment.
no code implementations • IJCNLP 2019 • Zixian Huang, Yulin Shen, Xiao Li, Yuang Wei, Gong Cheng, Lin Zhou, Xin-yu Dai, Yuzhong Qu
Scenario-based question answering (SQA) has attracted increasing research attention.