1 code implementation • 24 Oct 2023 • Shukang Yin, Chaoyou Fu, Sirui Zhao, Tong Xu, Hao Wang, Dianbo Sui, Yunhang Shen, Ke Li, Xing Sun, Enhong Chen
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with the image content.
1 code implementation • 3 Nov 2020 • Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Xiangrong Zeng, Shengping Liu
Compared with cross-entropy loss that highly penalizes small shifts in triple order, the proposed bipartite matching loss is invariant to any permutation of predictions; thus, it can provide the proposed networks with a more accurate training signal by ignoring triple order and focusing on relation types and entities.
Ranked #1 on Joint Entity and Relation Extraction on NYT
1 code implementation • IJCNLP 2019 • Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu
The lack of word boundaries information has been seen as one of the main obstacles to develop a high performance Chinese named entity recognition (NER) system.
Ranked #11 on Chinese Named Entity Recognition on Weibo NER
Chinese Named Entity Recognition named-entity-recognition +2
1 code implementation • ACL 2021 • Zhuoran Jin, Yubo Chen, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Jun Zhao
CogNet is a knowledge base that integrates three types of knowledge: linguistic knowledge, world knowledge and commonsense knowledge.
2 code implementations • ACL 2021 • Hang Yang, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang
We argue that sentence-level extractors are ill-suited to the DEE task where event arguments always scatter across sentences and multiple events may co-exist in a document.
1 code implementation • ACL 2022 • Zhuoran Jin, Tianyi Men, Hongbang Yuan, Zhitao He, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Yubo Chen, Jun Zhao
Designing CogKGE aims to provide a unified programming framework for KGE tasks and a series of knowledge representations for downstream tasks.
1 code implementation • ACL 2021 • Dianbo Sui, Zhengkun Tian, Yubo Chen, Kang Liu, Jun Zhao
In this paper, we aim to explore an uncharted territory, which is Chinese multimodal named entity recognition (NER) with both textual and acoustic contents.
1 code implementation • Findings (EMNLP) 2021 • Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao
In this paper, we propose a federated denoising framework to suppress label noise in federated settings.
no code implementations • NAACL 2021 • Dianbo Sui, Yubo Chen, Binjie Mao, Delai Qiu, Kang Liu, Jun Zhao
This is mainly due to the fact that human beings can leverage knowledge obtained from relevant tasks.
no code implementations • EMNLP 2020 • Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, Weijian Sun
In this paper, we propose a privacy-preserving medical relation extraction model based on federated learning, which enables training a central model with no single piece of private local data being shared or exchanged.
no code implementations • COLING 2020 • Jian Liu, Dianbo Sui, Kang Liu, Jun Zhao
Despite many advances, existing approaches for this task did not consider dialogue structure and background knowledge (e. g., relationships between speakers).
Ranked #6 on Question Answering on FriendsQA
no code implementations • EMNLP 2021 • Dianbo Sui, Chenhao Wang, Yubo Chen, Kang Liu, Jun Zhao, Wei Bi
In this paper, we formulate end-to-end KBP as a direct set generation problem, avoiding considering the order of multiple facts.
no code implementations • SemEval (NAACL) 2022 • Jia Fu, Zhen Gan, Zhucong Li, Sirui Li, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao
This paper describes our approach to develop a complex named entity recognition system in SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, Track 9 - Chinese.