3 citations · 3 across the 4 of their papers we have counts for
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cs.CL2023
Generative Calibration for In-context Learning
Zhongtao Jiang, Yuanzhe Zhang, Cao Liu +2
As one of the most exciting features of large language models (LLMs), in-context learning is a mixed blessing. While it allows users to fast-prototype a task solver with only a few…
cs.CL2019
Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss
Cao Liu, Kang Liu, Shizhu He +2
We tackle the task of question generation over knowledge bases. Conventional methods for this task neglect two crucial research issues: 1) the given predicate needs to be expressed…
cs.CL2019★ 3 cited
Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots
Cao Liu, Kang Liu, Shizhu He +2
Conventional chatbots focus on two-party response generation, which simplifies the real dialogue scene. In this paper, we strive toward a novel task of Response Generation on Multi…