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Temporal knowledge graph question answering (TKGQA) poses a significant challenge task, due to the temporal constraints hidden in questions and the answers sought from dynamic structured knowledge.
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Wenhu Chen, Xinyi Wang, and William Yang Wang. 2021 · 2021
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Zhen Jia, Soumajit Pramanik, Rishiraj Saha Roy, and Gerhard Weikum. 2021 · 2021
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Question answering over temporal knowledge graphs
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Tempoqr: Temporal question reasoning over knowledge graphs
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Improving time sensitivity for question answering over temporal knowledge graphs
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Once upon a time in graph: Relative-time pretraining for complex temporal reasoning
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Multi-source test-time adaptation as dueling bandits for extractive question answering
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Making large language models perform better in knowledge graph completion
Yichi Zhang, Zhuo Chen, Wen Zhang, and Huajun Chen. 2023 · 2023
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Knowledgeable parameter efficient tuning network for commonsense question answering
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Chain-of-knowledge: Grounding large language models via dynamic knowledge adapting over heterogeneous sources
Xingxuan Li, Ruochen Zhao, Yew Ken Chia, Bosheng Ding, Shafiq Joty, Soujanya Poria, and Lidong Bing. 2024 · 2024
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Large language models can learn temporal reasoning
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Give us the facts: Enhancing large language models with knowledge graphs for fact-aware language modeling
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Twirgcn: Temporally weighted graph convolution for question answering over temporal knowledge graphs
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