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Temporal Knowledge Graph (TKG) forecasting aims to predict future facts based on given histories.
Recurrent event network: Autoregressive structure inference over temporal knowledge graphs
Woojeong Jin, Meng Qu, Xisen Jin, and Xiang Ren. 2019 · 1904
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
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Icews coded event data
Elizabeth Boschee, Jennifer Lautenschlager, Sean O’Brien, Steve Shellman, James Starz, and Michael Ward. 2015 · 2015
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Multi-behavioral sequential prediction with recurrent log-bilinear model
Qiang Liu, Shu Wu, and Liang Wang. 2017 · 2017
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Know-evolve: Deep temporal reasoning for dynamic knowledge graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song. 2017 · 2017
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Learning sequence encoders for temporal knowledge graph completion
Alberto García-Durán, Sebastijan Dumančić, and Mathias Niepert. 2018 · 2018
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
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Graph hawkes neural network for forecasting on temporal knowledge graphs
Zhen Han, Yunpu Ma, Yuyi Wang, Stephan Günnemann, and Volker Tresp. 2020 · 2020
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Recurrent event network: Autoregressive structure inferenceover temporal knowledge graphs
W. Jin, M. Qu, X. Jin, and X. Ren. 2020 · 2020
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TimeTraveler: Reinforcement learning for temporal knowledge graph forecasting
Haohai Sun, Jialun Zhong, Yunpu Ma, Zhen Han, and Kun He. 2021 · 2021
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Learning from history: Modeling temporal knowledge graphs with sequential copy-generation networks
Cunchao Zhu, Muhao Chen, Changjun Fan, Guangquan Cheng, and Yan Zhang. 2021 · 2021
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Gptq: Accurate post-training quantization for generative pre-trained transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh. 2022 · 2022
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Enhanced temporal knowledge embeddings with contextualized language representations
Zhen Han, Ruotong Liao, Beiyan Liu, Yao Zhang, Zifeng Ding, Jindong Gu, Heinz Koeppl, Hinrich Schuetze, and Volker Tresp. 2022 · 2022
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Tirgn: Time-guided recurrent graph network with local-global historical patterns for temporal knowledge graph reasoning
Yujia Li, Shiliang Sun, and Jing Zhao. 2022 · 2022
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Tlogic: Temporal logical rules for explainable link forecasting on temporal knowledge graphs
Yushan Liu, Yunpu Ma, Marcel Hildebrandt, Mitchell Joblin, and Volker Tresp. 2022 · 2022
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Metatkg: Learning evolutionary meta-knowledge for temporal knowledge graph reasoning
Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, and Xiao-Yu Zhang. 2022 · 2022
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Temporal and heterogeneous graph neural network for financial time series prediction
Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, and Yuqi Liang. 2022 · 2022
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Mohamed Aghzal, Erion Plaku, and Ziyu Yao. 2023 · 2023
Enhancing document-level event argument extraction with contextual clues and role relevance
Wanlong Liu, Shaohuan Cheng, Dingyi Zeng, and Hong Qu. 2023 · 2023
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Language models can improve event prediction by few-shot abductive reasoning
Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y Zhang, Jun Zhou, Chenhao Tan, and Hongyuan Mei. 2023 · 2023
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Noise-robust semi-supervised learning for distantly supervised relation extraction
Xin Sun, Qiang Liu, Shu Wu, Zilei Wang, and Liang Wang. 2023 · 2023
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Towards benchmarking and improving the temporal reasoning capability of large language models
Qingyu Tan, Hwee Tou Ng, and Lidong Bing. 2023 · 2023
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Tram: Benchmarking temporal reasoning for large language models
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Multi-granularity temporal question answering over knowledge graphs
Ziyang Chen, Jinzhi Liao, and Xiang Zhao. 2023 · 2023
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Zero-shot relational learning on temporal knowledge graphs with large language models
Zifeng Ding, Heling Cai, Jingpei Wu, Yunpu Ma, Ruotong Liao, Bo Xiong, and Volker Tresp. 2023 · 2023
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Learning joint structural and temporal contextualized knowledge embeddings for temporal knowledge graph completion
Yifu Gao, Yongquan He, Zhigang Kan, Yi Han, Linbo Qiao, and Dongsheng Li. 2023 · 2023
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Do language models have a common sense regarding time? revisiting temporal commonsense reasoning in the era of large language models
Raghav Jain, Daivik Sojitra, Arkadeep Acharya, Sriparna Saha, Adam Jatowt, and Sandipan Dandapat. 2023 · 2023
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Structgpt: A general framework for large language model to reason over structured data
Jinhao Jiang, Kun Zhou, Zican Dong, Keming Ye, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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Temporal knowledge graph forecasting without knowledge using in-context learning
Dong-Ho Lee, Kian Ahrabian, Woojeong Jin, Fred Morstatter, and Jay Pujara. 2023 · 2023
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Yuqing Wang and Yun Zhao. 2023 · 2023
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Back to the future: Towards explainable temporal reasoning with large language models
Chenhan Yuan, Qianqian Xie, Jimin Huang, and Sophia Ananiadou. 2023 · 2023
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Learning long-and short-term representations for temporal knowledge graph reasoning
Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, and Liang Wang. 2023b · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al. 2024 · 2024
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Beyond single-event extraction: Towards efficient document-level multi-event argument extraction
Wanlong Liu, Li Zhou, Dingyi Zeng, Yichen Xiao, Shaohuan Cheng, Chen Zhang, Grandee Lee, Malu Zhang, and Wenyu Chen. 2024 · 2024
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Camlo: Cross-attentive multi-view network for long-term origin-destination flow prediction
Liang Wang, Hao Fu, Shu Wu, Qiang Liu, Xuelei Tan, Fangsheng Huang, Mengdi Zhang, and Wei Wu. 2024 · 2024
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Metatkg++: Learning evolving factor enhanced meta-knowledge for temporal knowledge graph reasoning
Yuwei Xia, Mengqi Zhang, Qiang Liu, Liang Wang, Shu Wu, Xiaoyu Zhang, and Liang Wang. 2024 · 2024
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Large language models can learn temporal reasoning
Siheng Xiong, Ali Payani, Ramana Kompella, and Faramarz Fekri. 2024 · 2024
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