1 code implementation • ACL 2018 • Xiangrong Zeng, Daojian Zeng, Shizhu He, Kang Liu, Jun Zhao
The relational facts in sentences are often complicated.
Ranked #12 on Relation Extraction on NYT11-HRL
no code implementations • IJCNLP 2019 • Xiangrong Zeng, Shizhu He, Daojian Zeng, Kang Liu, Shengping Liu, Jun Zhao
Existing works didn{'}t consider the extraction order of relational facts in a sentence.
2 code implementations • 24 Nov 2019 • Daojian Zeng, Ranran Haoran Zhang, Qianying Liu
The model is extremely weak at differing the head and tail entity, resulting in inaccurate entity extraction.
Ranked #12 on Relation Extraction on WebNLG
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi
We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.
no code implementations • 13 Jan 2022 • Chao Zhao, Daojian Zeng, Lu Xu, Jianhua Dai
Document-level Relation Extraction (DRE) aims to recognize the relations between two entities.
Ranked #5 on Relation Extraction on CDR
no code implementations • 28 Feb 2024 • Jiachun Li, Pengfei Cao, Chenhao Wang, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao
Large language models exhibit high-level commonsense reasoning abilities, especially with enhancement methods like Chain-of-Thought (CoT).
no code implementations • 29 Feb 2024 • Hongbang Yuan, Pengfei Cao, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao
Large Language Models (LLMs) have shown impressive capabilities but still suffer from the issue of hallucinations.