no code implementations • 18 Mar 2024 • Qinghua Zhao, Jiaang Li, Lei LI, Zenghui Zhou, Junfeng Liu
Existing works have studied the impacts of the order of words within natural text.
no code implementations • 1 Mar 2024 • Bo Li, Qinghua Zhao, Lijie Wen
Probing the memorization of large language models holds significant importance.
no code implementations • 1 Mar 2024 • Qinghua Zhao, Vinit Ravishankar, Nicolas Garneau, Anders Søgaard
Word order is an important concept in natural language, and in this work, we study how word order affects the induction of world knowledge from raw text using language models.
1 code implementation • 18 Aug 2022 • Qinghua Zhao, Shuai Ma, Yuxuan Lei
On the one hand, it is implicit and only model weights are paid attention to, the pre-trained entity embeddings are ignored.
1 code implementation • 28 Feb 2022 • Qinghua Zhao, Shuai Ma
In this paper, we study sentiment analysis task where the outcomes are mainly contributed by a few key elements of the inputs.
1 code implementation • 24 Feb 2022 • Qinghua Zhao, Shuai Ma, Shuo Ren
On the contrary, the second task predicts the overall sentiment polarity given the sentiment polarity of the word as prior knowledge.
1 code implementation • 19 Dec 2021 • Qinghua Zhao
News recommendation models often fall short in capturing users' preferences due to their static approach to user-news interactions.
1 code implementation • ACL 2021 • Shan Yang, Yongfei Zhang, Guanglin Niu, Qinghua Zhao, ShiLiang Pu
Few-shot relation extraction (FSRE) is of great importance in long-tail distribution problem, especially in special domain with low-resource data.