1 code implementation • 26 Jan 2024 • Haochen Tan, Zhijiang Guo, Zhan Shi, Lu Xu, Zhili Liu, Yunlong Feng, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, Linqi Song
LLMs are prompted to generate extensive content in response to these meta-questions.
no code implementations • 13 May 2023 • Haochen Tan, Han Wu, Wei Shao, Xinyun Zhang, Mingjie Zhan, Zhaohui Hou, Ding Liang, Linqi Song
Meetings typically involve multiple participants and lengthy conversations, resulting in redundant and trivial content.
no code implementations • 12 May 2023 • Xinyun Zhang, Haochen Tan, Han Wu, Bei Yu
To inject visual knowledge into PLMs, existing methods incorporate either the text or image encoder of vision-language models (VLMs) to encode the visual information and update all the original parameters of PLMs for knowledge fusion.
1 code implementation • 9 May 2023 • Han Wu, Mingjie Zhan, Haochen Tan, Zhaohui Hou, Ding Liang, Linqi Song
Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data.
1 code implementation • 29 May 2022 • Han Wu, Haochen Tan, Mingjie Zhan, Gangming Zhao, Shaoqing Lu, Ding Liang, Linqi Song
Existing dialogue modeling methods have achieved promising performance on various dialogue tasks with the aid of Transformer and the large-scale pre-trained language models.
1 code implementation • Findings (NAACL) 2022 • Han Wu, Haochen Tan, Kun Xu, Shuqi Liu, Lianwei Wu, Linqi Song
While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of multilingual CSRL annotations for the parser training.
1 code implementation • Findings (ACL) 2022 • Haochen Tan, Wei Shao, Han Wu, Ke Yang, Linqi Song
Contrastive learning has shown great potential in unsupervised sentence embedding tasks, e. g., SimCSE.
no code implementations • EMNLP 2020 • Kun Xu, Haochen Tan, Linfeng Song, Han Wu, Haisong Zhang, Linqi Song, Dong Yu
For multi-turn dialogue rewriting, the capacity of effectively modeling the linguistic knowledge in dialog context and getting rid of the noises is essential to improve its performance.