no code implementations • 4 Dec 2015 • Yantao Jia, Yuanzhuo Wang, Hailun Lin, Xiaolong Jin, Xue-Qi Cheng
Knowledge graph embedding aims to represent entities and relations in a large-scale knowledge graph as elements in a continuous vector space.
no code implementations • Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) 2016 • Tong Man, Hua-Wei Shen, Shenghua Liu, Xiaolong Jin, and Xueqi Cheng
Predicting anchor links across social networks has important implications to an array of applications, including cross-network information diffusion and cross-domain recommendation.
no code implementations • ACL 2018 • Yue Zhao, Xiaolong Jin, Yuanzhuo Wang, Xue-Qi Cheng
Document-level information is very important for event detection even at sentence level.
no code implementations • IJCNLP 2019 • Haoran Yan, Xiaolong Jin, Xiangbin Meng, Jiafeng Guo, Xue-Qi Cheng
Syntactic relations are broadly used in many NLP tasks.
no code implementations • ACL 2020 • Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, Xue-Qi Cheng
It aims to infer an unknown element in a partial fact consisting of the primary triple coupled with any number of its auxiliary description(s).
no code implementations • COLING 2020 • Yutao Zeng, Xiaolong Jin, Saiping Guan, Jiafeng Guo, Xueqi Cheng
To resolve event coreference, existing methods usually calculate the similarities between event mentions and between specific kinds of event arguments.
1 code implementation • 21 Apr 2021 • Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, Xueqi Cheng
However, they mainly focus on link prediction on binary relational data, where facts are usually represented as triples in the form of (head entity, relation, tail entity).
1 code implementation • 21 Apr 2021 • Zixuan Li, Xiaolong Jin, Wei Li, Saiping Guan, Jiafeng Guo, HuaWei Shen, Yuanzhuo Wang, Xueqi Cheng
To capture these properties effectively and efficiently, we propose a novel Recurrent Evolution network based on Graph Convolution Network (GCN), called RE-GCN, which learns the evolutional representations of entities and relations at each timestamp by modeling the KG sequence recurrently.
no code implementations • ACL 2021 • Zixuan Li, Xiaolong Jin, Saiping Guan, Wei Li, Jiafeng Guo, Yuanzhuo Wang, Xueqi Cheng
Specifically, at the clue searching stage, CluSTeR learns a beam search policy via reinforcement learning (RL) to induce multiple clues from historical facts.
1 code implementation • EMNLP 2021 • Long Bai, Saiping Guan, Jiafeng Guo, Zixuan Li, Xiaolong Jin, Xueqi Cheng
In this paper, we propose a Transformer-based model, called MCPredictor, which integrates deep event-level and script-level information for script event prediction.
1 code implementation • 31 Dec 2021 • Saiping Guan, Xueqi Cheng, Long Bai, Fujun Zhang, Zixuan Li, Yutao Zeng, Xiaolong Jin, Jiafeng Guo
Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG).
1 code implementation • ACL 2022 • Zixuan Li, Saiping Guan, Xiaolong Jin, Weihua Peng, Yajuan Lyu, Yong Zhu, Long Bai, Wei Li, Jiafeng Guo, Xueqi Cheng
Furthermore, these models are all trained offline, which cannot well adapt to the changes of evolutional patterns from then on.
no code implementations • 18 Oct 2022 • Zixuan Li, Zhongni Hou, Saiping Guan, Xiaolong Jin, Weihua Peng, Long Bai, Yajuan Lyu, Wei Li, Jiafeng Guo, Xueqi Cheng
This is actually a matching task between a query and candidate entities based on their historical structures, which reflect behavioral trends of the entities at different timestamps.
1 code implementation • 16 Dec 2022 • Long Bai, Saiping Guan, Zixuan Li, Jiafeng Guo, Xiaolong Jin, Xueqi Cheng
Fundamentally, it is based on the proposed rich event description, which enriches the existing ones with three kinds of important information, namely, the senses of verbs, extra semantic roles, and types of participants.
no code implementations • 10 May 2023 • Jiyao Wei, Saiping Guan, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
Thus, we introduce a new task, Few-Shot Link Prediction on Hyper-relational Facts (FSLPHFs).
no code implementations • 22 May 2023 • Zhilei Hu, Zixuan Li, Xiaolong Jin, Long Bai, Saiping Guan, Jiafeng Guo, Xueqi Cheng
This is a very challenging task, because causal relations are usually expressed by implicit associations between events.
1 code implementation • 22 Sep 2023 • Weicheng Ren, Zixuan Li, Xiaolong Jin, Long Bai, Miao Su, Yantao Liu, Saiping Guan, Jiafeng Guo, Xueqi Cheng
Since existing NEE datasets (e. g., Genia11) are limited to specific domains and contain a narrow range of event types with nested structures, we systematically categorize nested events in the generic domain and construct a new NEE dataset, called ACE2005-Nest.
no code implementations • 22 Sep 2023 • Zhilei Hu, Zixuan Li, Daozhu Xu, Long Bai, Cheng Jin, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
To comprehensively understand their intrinsic semantics, in this paper, we obtain prototype representations for each type of event relation and propose a Prototype-Enhanced Matching (ProtoEM) framework for the joint extraction of multiple kinds of event relations.
no code implementations • 22 Oct 2023 • Yantao Liu, Zixuan Li, Xiaolong Jin, Yucan Guo, Long Bai, Saiping Guan, Jiafeng Guo, Xueqi Cheng
The Knowledge Base Question Answering (KBQA) task aims to answer natural language questions based on a given knowledge base.
no code implementations • 6 Nov 2023 • Yucan Guo, Zixuan Li, Xiaolong Jin, Yantao Liu, Yutao Zeng, Wenxuan Liu, Xiang Li, Pan Yang, Long Bai, Jiafeng Guo, Xueqi Cheng
Therefore, in this paper, we propose a universal retrieval-augmented code generation framework based on LLMs, called Code4UIE, for IE tasks.
no code implementations • 25 Jan 2024 • Xiaolong Jin, Zhuo Zhang, Xiangyu Zhang
Given the low cost of our method, we are able to conduct a large scale study regarding LLM alignment issues in different worlds.
no code implementations • 12 Mar 2024 • Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren, Wenxuan Liu, Miao Su, Yucan Guo, Yantao Liu, Xiang Li, Zhilei Hu, Long Bai, Wei Li, Yidan Liu, Pan Yang, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
After instruction tuning, KnowCoder further exhibits strong generalization ability on unseen schemas and achieves up to $\textbf{12. 5%}$ and $\textbf{21. 9%}$, compared to sota baselines, under the zero-shot setting and the low resource setting, respectively.
no code implementations • 2 Apr 2024 • Zhongni Hou, Xiaolong Jin, Zixuan Li, Long Bai, Jiafeng Guo, Xueqi Cheng
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently.
no code implementations • 2 Apr 2024 • Kailin Zhao, Xiaolong Jin, Long Bai, Jiafeng Guo, Xueqi Cheng
Therefore, this paper proposes a new task, called class-incremental few-shot event detection.
no code implementations • 2 Apr 2024 • Zhuo Chen, Zhao Zhang, Zixuan Li, Fei Wang, Yutao Zeng, Xiaolong Jin, Yongjun Xu
Temporal Knowledge Graph Question Answering (TKGQA) aims to answer questions with temporal intent over Temporal Knowledge Graphs (TKGs).
no code implementations • COLING 2022 • Kailin Zhao, Xiaolong Jin, Saiping Guan, Jiafeng Guo, Xueqi Cheng
For the meta learner, it requires a good generalization ability so as to quickly adapt to new tasks.