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Large language models (LLMs) have shown remarkable generalization capability with exceptional performance in various language modeling tasks.
A learning algorithm for continually running fully recurrent neural networks
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The unified medical language system (UMLS): integrating biomedical terminology
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Translating embeddings for modeling multi-relational data
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An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
Tsatsaronis, G.; Balikas, G.; Malakasiotis, P.; Partalas, I.; Zschunke, M.; Alvers, M. R.; Weissenborn, D.; Krithara, A.; Petridis, S.; Polychronopoulos, D.; et al. 2015 · 2015
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Conceptnet 5.5: An open multilingual graph of general knowledge
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Universal language model fine-tuning for text classification
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Can a suit of armor conduct electricity? a new dataset for open book question answering
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Knowledgeable reader: Enhancing cloze-style reading comprehension with external commonsense knowledge
Mihaylov, T.; and Frank, A. 2018 · 2018
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Graph attention networks
Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2018 · 2018
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Pubmedqa: A dataset for biomedical research question answering
Jin, Q.; Dhingra, B.; Liu, Z.; Cohen, W. W.; and Lu, X. 2019 · 2019
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Kagnet: Knowledge-aware graph networks for commonsense reasoning
Lin, B. Y.; Chen, X.; Chen, J.; and Ren, X. 2019 · 2019
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Improving natural language inference using external knowledge in the science questions domain
Wang, X.; Kapanipathi, P.; Musa, R.; Yu, M.; Talamadupula, K.; Abdelaziz, I.; Chang, M.; Fokoue, A.; Makni, B.; Mattei, N.; et al. 2019 · 2019
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Piqa: Reasoning about physical commonsense in natural language
Bisk, Y.; Zellers, R.; Gao, J.; Choi, Y.; et al. 2020 · 2020
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Language models are few-shot learners
Brown, T.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J. D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 2020
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Scalable multi-hop relational reasoning for knowledge-aware question answering
Feng, Y.; Chen, X.; Lin, B. Y.; Wang, P.; Yan, J.; and Ren, X. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Lewis, P.; Perez, E.; Piktus, A.; Petroni, F.; Karpukhin, V.; Goyal, N.; Küttler, H.; Lewis, M.; Yih, W.-t.; Rocktäschel, T.; et al. 2020 · 2020
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Graph-based reasoning over heterogeneous external knowledge for commonsense question answering
Lv, S.; Guo, D.; Xu, J.; Tang, D.; Duan, N.; Gong, M.; Shou, L.; Jiang, D.; Cao, G.; and Hu, S. 2020 · 2020
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A survey on knowledge graphs: Representation, acquisition, and applications
Ji, S.; Pan, S.; Cambria, E.; Marttinen, P.; and Philip, S. Y. 2021 · 2021
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Jointgt: Graph-text joint representation learning for text generation from knowledge graphs
Ke, P.; Ji, H.; Ran, Y.; Cui, X.; Wang, L.; Song, L.; Zhu, X.; and Huang, M. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Lester, B.; Al-Rfou, R.; and Constant, N. 2021 · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Li, X. L.; and Liang, P. 2021 · 2021
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RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge
Lin, B. Y.; Wu, Z.; Yang, Y.; Lee, D.-H.; and Ren, X. 2021 · 2021
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Lego: Latent execution-guided reasoning for multi-hop question answering on knowledge graphs
Jaket: Joint pre-training of knowledge graph and language understanding
Yu, D.; Zhu, C.; Yang, Y.; and Zeng, M. 2022 · 2022
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GreaseLM: Graph REASoning Enhanced Language Models for Question Answering
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Anil, R.; Dai, A. M.; Firat, O.; Johnson, M.; Lepikhin, D.; Passos, A.; Shakeri, S.; Taropa, E.; Bailey, P.; Chen, Z.; et al. 2023 · 2023
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Ernie 3.0: Large-scale knowledge enhanced pre-training for language understanding and generation
Sun, Y.; Wang, S.; Feng, S.; Ding, S.; Pang, C.; Shang, J.; Liu, J.; Chen, X.; Zhao, Y.; Lu, Y.; et al. 2021 · 2021
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QA-GNN: Reasoning with language models and knowledge graphs for question answering
Yasunaga, M.; Ren, H.; Bosselut, A.; Liang, P.; and Leskovec, J. 2021 · 2021
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Retrieving and reading: A comprehensive survey on open-domain question answering
Zhu, F.; Lei, W.; Wang, C.; Zheng, J.; Poria, S.; and Chua, T.-S. 2021 · 2021
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Scaling instruction-finetuned language models
Chung, H. W.; Hou, L.; Longpre, S.; Zoph, B.; Tay, Y.; Fedus, W.; Li, E.; Wang, X.; Dehghani, M.; Brahma, S.; et al. 2022 · 2022
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LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2022 · 2022
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CrowdGraph: A Crowdsourcing Multi-Modal Knowledge Graph Approach to Explainable Fauxtography Detection
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DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
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Survey of hallucination in natural language generation
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Unifying Large Language Models and Knowledge Graphs: A Roadmap
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Leveraging large language models for multiple choice question answering
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Mededit: Model editing for medical question answering with external knowledge bases
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Llama: Open and efficient foundation language models
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Knowledge Graph Prompting for Multi-Document Question Answering
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A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability
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Benchmarking large language models for news summarization
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A survey of large language models
Zhao, W. X.; Zhou, K.; Li, J.; Tang, T.; Wang, X.; Hou, Y.; Min, Y.; Zhang, B.; Zhang, J.; Dong, Z.; et al. 2023 · 2023
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LLMRec: Large Language Models with Graph Augmentation for Recommendation
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