Meta-PKE: Memory-Enhanced Task-Adaptive Personal Knowledge Extraction in Daily Life

Survey of Hallucination in Natural Language Generation

Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023) · ACM Computing Surveys · doi:10.1145/3571730 · Cited by 5,025 · see citing works

LLaMA: Open and Efficient Foundation Language Models

Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., et al. (2023) · arXiv · doi:10.48550/arxiv.2302.13971 · Cited by 4,602 · see citing works

A Survey of Large Language Models

Zhao, W. X., Zhou, K., Li, J., Tang, T., Dong, Z., Hou, Y., Zhang, B., Min, Y., Zhang, J., Liu, P., et al. (2026) · Frontiers of Computer Science · doi:10.1007/s11704-026-60308-3 · Cited by 2,093 · see citing works

Unifying Large Language Models and Knowledge Graphs: A Roadmap

Pan, S., Luo, L., Wang, Y., Chen, C., Wang, J., & Wu, X. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3352100 · Cited by 1,376 · see citing works

Entity, Relation, and Event Extraction with Contextualized Span Representations

Wadden, D., Wennberg, U., Luan, Y., & Hajishirzi, H. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1585 · Cited by 625 · see citing works

ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports

Jeblick, K., Schachtner, B., Dexl, J., Mittermeier, A., Stüber, A. T., Topalis, J., Weber, T., Wesp, P., Sabel, B. O., Ricke, J., et al. (2023) · European Radiology · doi:10.1007/s00330-023-10213-1 · Cited by 549 · see citing works

GPT-NER: Named Entity Recognition via Large Language Models

Wang, S.-H., Sun, X., Li, X., Ouyang, R., Wu, F., Zhang, T.-W., Li, J., Wang, G.-Y., & Guo, C. (2023) · North American Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2025.findings-naacl.239 · Cited by 508 · see citing works

Unified Structure Generation for Universal Information Extraction

Lu, Y., Liu, Q., Dai, D., Xiao, X., Lin, H., Han, X., Sun, L., & Wu, H. R. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.395 · Cited by 481 · see citing works

Findings of the Association for Computational Linguistics: ACL 2022

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KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction

Chen, X., Zhang, N., Xie, X., Deng, S., Yao, Y., Tan, C., Huang, F., Si, L., & Chen, H. (2022) · Proceedings of the ACM Web Conference 2022 · doi:10.1145/3485447.3511998 · Cited by 389 · see citing works

A Unified Generative Framework for Aspect-based Sentiment Analysis

Yan, H. R., Dai, J., Ji, T., Qiu, X., & Zhang, Z. (2021) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2021.acl-long.188 · Cited by 365 · see citing works

Abductive Commonsense ReasoningPreprint

Bhagavatula, C., Bras, R. J. L., Malaviya, C., Sakaguchi, K., Holtzman, A., Rashkin, H., Downey, D., Yih, S., & Choi, Y. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.05739 · Cited by 331 · see citing works

Large language models for generative information extraction: a survey

Xu, D., Chen, W., Peng, W., Zhang, C., Xu, T., Zhao, X., Wu, X., Zheng, Y., Wang, Y., & Chen, E. (2024) · Frontiers of Computer Science · doi:10.1007/s11704-024-40555-y · Cited by 326 · see citing works

SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation

Gong, F., Wang, M., Wang, H., Wang, S., & Liu, M. (2020) · Big Data Research · doi:10.1016/j.bdr.2020.100174 · Cited by 254 · see citing works

GoLLIE: Annotation Guidelines improve Zero-Shot Information-ExtractionPreprint

Sainz, O., García-Ferrero, I., Agerri, R., de Lacalle, O. L., Rigau, G., & Agirre, E. (2023) · International Conference on Learning Representations · doi:10.48550/arxiv.2310.03668 · Cited by 244 · see citing works

Exploiting Linked Data and Knowledge Graphs in Large Organisations

Wu, H., Gómez-Pérez, J. M., Vetere, G., & Pan, J. Z. (2017) · Springer eBooks · doi:10.1007/978-3-319-45654-6 · Cited by 220 · see citing works

InstructUIE: Multi-task Instruction Tuning for Unified Information ExtractionPreprint

Wang, X., Zhou, W., Zu, C., Xia, H., Chen, T., Zhang, Y., Zheng, R., Ye, J., Zhang, Q., Gui, T., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2304.08085 · Cited by 210 · see citing works

GPT-RE: In-context Learning for Relation Extraction using Large Language Models

Wan, Z., Cheng, F., Mao, Z., Liu, Q., Song, H., Li, J., & Kurohashi, S. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.214 · Cited by 199 · see citing works

Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

Zhang, W., Paudel, B., Wang, L., Chen, J., Zhu, H. J., Zhang, W., Bernstein, A., & Chen, H. (2019) · International World Wide Web Conference (WWW) · doi:10.1145/3308558.3313612 · Cited by 186 · see citing works

A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series ModelsPreprint

Ye, J., Chen, X., Xu, N., Zu, C., Shao, Z., Liu, S., Cui, Y., Zhou, Z., Gong, C., Shen, Y., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2303.10420 · Cited by 180 · see citing works

ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTPreprint

Wei, X., Cui, X., Cheng, N., Wang, X., Zhang, X., Huang, S., Xie, P., Xu, J., Chen, Y., Zhang, M., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2302.10205 · Cited by 157 · see citing works

GPT-NER: Named Entity Recognition via Large Language ModelsPreprint

Wang, S., Sun, X., Li, X., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2304.10428 · Cited by 144 · see citing works

Virtual Knowledge Graphs: An Overview of Systems and Use Cases

Xiao, G., Ding, L., Cogrel, B., & Calvanese, D. (2019) · Data Intelligence · doi:10.1162/dint_a_00011 · Cited by 141 · see citing works

Code4Struct: Code Generation for Few-Shot Event Structure Prediction

Wang, X., Li, S., & Ji, H. (2022) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2023.acl-long.202 · Cited by 132 · see citing works

Baichuan 2: Open Large-scale Language Models

Yang, A., Xiao, B., Wang, B., Zhang, B., Bian, C., Yin, C., Lv, C., Pan, D., Wang, D., Yan, D., et al. (2023) · arXiv · doi:10.48550/arxiv.2309.10305 · Cited by 125 · see citing works

How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding TasksPreprint

Chen, X., Ye, J., Zu, C., Xu, N., Zheng, R., Peng, M.-L., Zhou, J., Gui, T., Zhang, Q., & Huang, X. (2023) · arXiv.org · doi:10.48550/arxiv.2303.00293 · Cited by 116 · see citing works

RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction

Chia, Y. K., Bing, L., Poria, S., & Si, L. (2022) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2022.findings-acl.5 · Cited by 109 · see citing works

CodeKGC: Code Language Model for Generative Knowledge Graph Construction

Bi, Z., Chen, J., Jiang, Y., Xiong, F., Guo, W., Chen, H., & Zhang, N. (2024) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3641850 · Cited by 94 · see citing works

DuIE: A Large-Scale Chinese Dataset for Information Extraction

Li, S., He, W. P., Shi, Y., Jiang, W., Liang, H., Jiang, Y., Zhang, Y., Lyu, Y., & Zhu, Y. T. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-32236-6_72 · Cited by 91 · see citing works

LLMs Accelerate Annotation for Medical Information ExtractionPreprint

Goel, A., Gueta, A., Gilon, O., Liu, C., Erell, S., Nguyen, L. H., Hao, X., Jaber, B., Reddy, S., Kartha, R., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2312.02296 · Cited by 86 · see citing works

Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System

Gao, Y., Sheng, T., Xiang, Y., Xiong, Y., Wang, H., & Zhang, J. (2023) · arXiv · doi:10.48550/arxiv.2303.14524 · Cited by 79 · see citing works

Recurrent convolutional neural network for answer selection in community question answering

Zhou, X., Hu, B., Chen, Q., & Wang, X. (2017) · Neurocomputing · doi:10.1016/j.neucom.2016.07.082 · Cited by 78 · see citing works

Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors

Zhang, K., Gutiérrez, B. J., & Su, Y. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.50 · Cited by 77 · see citing works

Universal Information Extraction as Unified Semantic Matching

Lou, J., Lu, Y., Dai, D., Jia, W., Lin, H., Han, X., Sun, L., & Wu, H. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i11.26563 · Cited by 73 · see citing works

Twenty-five years of information extraction

Grishman, R. (2019) · Natural Language Engineering · doi:10.1017/s1351324919000512 · Cited by 70 · see citing works

How would Stance Detection Techniques Evolve after the Launch of ChatGPT?Preprint

Zhang, B., Ding, D., Jing, L., Dai, G., & Yin, N. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2212.14548 · Cited by 68 · see citing works

DuEE: A Large-Scale Dataset for Chinese Event Extraction in Real-World Scenarios

Li, X., Li, F., Pan, L., Chen, Y., Peng, W., Wang, Q., Lyu, Y., & Zhu, Y. T. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60457-8_44 · Cited by 68 · see citing works

TSVFN: Two-Stage Visual Fusion Network for multimodal relation extraction

Zhao, Q., Gao, T., & Guo, N. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103264 · Cited by 58 · see citing works

Multi-granularity cross-modal representation learning for named entity recognition on social media

Liu, P., Wang, G., Li, H., Liu, J., Ren, Y., Zhu, H., & Sun, L. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103546 · Cited by 58 · see citing works

Retrieval-Augmented Code Generation for Universal Information Extraction

Guo, Y., Li, Z., Jin, X., Liu, Y., Zeng, Y., Liu, W., Li, X., Pan, Y., Bai, L., Guo, J., et al. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-9434-8_3 · Cited by 46 · see citing works

Event Extraction as Question Generation and Answering

Di, L., Ran, S., Tetreault, J., & Jaimes, A. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.143 · Cited by 43 · see citing works

ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification

Zhou, Y., Shen, T., Geng, X., Long, G., & Jiang, D. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.183 · Cited by 41 · see citing works

An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks

Wu, Y., Zhao, Y. Q., Hu, B., Minervini, P., Stenetorp, P., & Riedel, S. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.346 · Cited by 39 · see citing works

A Survey on Neural Open Information Extraction: Current Status and Future Directions

Zhou, S., Yu, B., Sun, A., Long, C., Li, J., & Sun, J. (2022) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2022/793 · Cited by 37 · see citing works

Multi-modal news event detection with external knowledge

Lin, Z., Xie, J., & Li, Q. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103697 · Cited by 32 · see citing works

Revisiting the Negative Data of Distantly Supervised Relation Extraction

Xie, C., Liang, J., Liu, J., Huang, C., Huang, W., & Xiao, Y. (2021) · doi:10.18653/v1/2021.acl-long.277 · Cited by 29 · see citing works

Note the hierarchy: Taxonomy-guided prototype for few-shot named entity recognition

Feng, J., Xu, G., Wang, Q., Yang, Y., & Huang, L. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103557 · Cited by 25 · see citing works

EACE: A document-level event argument extraction model with argument constraint enhancement

Zhou, J., Shuang, K., Wang, Q., & Yao, X. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103559 · Cited by 24 · see citing works

MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective

Wang, X., Dou, S., Xiong, L., Zou, Y., Zhang, Q., Gui, T., Qiao, L., Cheng, Z., & Huang, X. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.383 · Cited by 23 · see citing works

Joint inter-word and inter-sentence multi-relation modeling for summary-based recommender system

Li, D., Deng, C., Wang, X., Li, Z., Zheng, C., Wang, J., & Li, B. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2023.103631 · Cited by 22 · see citing works

An adaptive category-aware recommender based on dual knowledge graphs

Xu, Y., Tian, L., Yang, Y., Chen, W., & Yue, L. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2023.103636 · Cited by 20 · see citing works

A hierarchical convolutional model for biomedical relation extraction

Hu, Y., Chen, Y., Huang, R., Qin, Y., & Zheng, Q. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103560 · Cited by 19 · see citing works

Document-level denoising relation extraction with false-negative mining and reinforced positive-class knowledge distillation

Zeng, D., Zhu, J., Chen, H., Dai, J., & Jiang, L. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103533 · Cited by 18 · see citing works

Multimodal joint learning for personal knowledge base construction from Twitter-based lifelogs

Yen, A.-Z., Huang, H., & Chen, H. (2019) · Information Processing & Management · doi:10.1016/j.ipm.2019.102148 · Cited by 17 · see citing works

ESGNet: A multimodal network model incorporating entity semantic graphs for information extraction from Chinese resumes

Luo, S. N., & Yu, J. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103524 · Cited by 15 · see citing works

EPIC: An epidemiological investigation of COVID-19 dataset for Chinese named entity recognition

Li, P., Zhou, G., Guo, Y., Zhang, S., Jiang, Y., & Tang, Y. Z. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103541 · Cited by 14 · see citing works

Context-Aware Prompt for Generation-based Event Argument Extraction with Diffusion Models

Luo, L., & Xu, Y. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3614820 · Cited by 13 · see citing works

Debiasing Generative Named Entity Recognition by Calibrating Sequence Likelihood

Xia, Y., Zhao, Y., Wu, W., & Li, S. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.98 · Cited by 10 · see citing works

SeqGPT: An Out-of-the-Box Large Language Model for Open Domain Sequence Understanding

Yu, T., Jiang, C., Lou, C., Huang, S., Wang, X., Liu, W., Cai, J., Li, Y., Li, Y., Tu, K., et al. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i17.29917 · Cited by 10 · see citing works

Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction

Qi, J., Zhang, C., Wang, X., Zeng, K., Yu, J., Liu, J., Hou, L., Li, J., & Xu, B. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.360 · Cited by 6 · see citing works

LED: A Dataset for Life Event Extraction from Dialogs

Chen, Y.-P., Yen, A.-Z., Huang, H., Nakayama, H., & Chen, H. (2023) · Findings of the Association for Computational Linguistics: EACL · doi:10.18653/v1/2023.findings-eacl.29 · Cited by 4 · see citing works

GIELLM: Japanese General Information Extraction Large Language Model Utilizing Mutual Reinforcement EffectPreprint

Gan, C., Zhang, Q., & Mori, T. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2311.06838 · Cited by 1 · see citing works

ODDA: An OODA-Driven Diverse Data Augmentation Framework for Low-Resource Relation Extraction

Zhong, Y., Gao, Y., Zhang, X., & Wang, H. (2025) · Findings of the Association for Computational Linguistics: ACL 2025 · doi:10.18653/v1/2025.findings-acl.15 · Cited by 3 · see citing works

A framework for hallucination mitigation in domain-specialized large language models with application to aviation maintenance decision support

Lu, X., Su, X., Feng, J., Zeng, K., Zhang, S., & Zhang, Y. (2026) · Information Processing & Management · doi:10.1016/j.ipm.2026.104762 · Cited by 3 · see citing works

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues

Zhong, Y., Gao, Y., & Wang, H. (2026) · Proceedings of the ACM Web Conference 2026 · doi:10.1145/3774904.3792089 · Cited by 1 · see citing works

Scene-aware memory discrimination: Deciding which personal knowledge stays

Zhong, Y., Guo, M., Wang, Z., Li, Z., Tu, D., & Wang, H. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115496 · Cited by 1 · see citing works

Extracting personal information from conversations

Tigunova, A. (2023) · Institution of Engineering and Technology eBooks · doi:10.1049/pbpc063e_ch9

Automated Extraction of Personal Knowledge from Smartphone Push Notifications

Li, Y., Yang, Z., Guo, Y., Chen, X., Agarwal, Y., & Hong, J. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8621866 · Cited by 8 · see citing works

Exploring Personal Knowledge Extraction from Conversations with CHARM

Tigunova, A., Mirza, P., Yates, A., & Weikum, G. (2021) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3437963.3441699 · Cited by 5 · see citing works

Universal Information Extraction with Meta-Pretrained Self-RetrievalPreprint

Yu, X., Fang, M., Liu, T., Yu, H., Hu, Z., Huang, F., Li, Y., & Wang, B. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2306.10444 · Cited by 1 · see citing works

DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base PopulationPreprint

Zhang, N., Xu, X., Tao, L., Yu, H., Ye, H., Qiao, S., Xie, X., Chen, X., Li, Z., Li, L., et al. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2201.03335 · Cited by 15 · see citing works