Search Results for author: Xiaolong Jin

Found 13 papers, 5 papers with code

Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning

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.

What is Event Knowledge Graph: A Survey

1 code implementation31 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).

Question Answering Text Generation

Integrating Deep Event-Level and Script-Level Information for Script Event Prediction

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.

Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs

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.

Knowledge Graphs

Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

1 code implementation21 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.

Representation Learning

Link Prediction on N-ary Relational Data Based on Relatedness Evaluation

1 code implementation21 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).

Knowledge Graphs Link Prediction

Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings

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.

Coreference Resolution Event Coreference Resolution

NeuInfer: Knowledge Inference on N-ary Facts

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).

Locally Adaptive Translation for Knowledge Graph Embedding

no code implementations4 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.

Knowledge Graph Embedding Knowledge Graphs +1

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