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Model editing aims to precisely alter the behaviors of large language models (LLMs) in relation to specific knowledge, while leaving unrelated knowledge intact.
Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting. 2023 · 1940
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Language Models as Knowledge Bases?. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . 2463–2473
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DRKG - Drug Repurposing Knowledge Graph for Covid-19
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Editing Factual Knowledge in Language Models. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing . 6491–6506
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Transformer Feed-Forward Layers Are Key-Value Memories. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing . 5484–5495
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Knowledge Neurons in Pretrained Transformers. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, Dublin, Ireland, 8493–8502
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Calibrating Factual Knowledge in Pretrained Language Models
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Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing . 30–45
Mor Geva, Avi Caciularu, Kevin Wang, and Yoav Goldberg. 2022 · 2022
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Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. In NeurIPS 2022 Workshop on Robustness in Sequence Modeling
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Locating and Editing Factual Associations in GPT
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Mass-Editing Memory in a Transformer
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Direct and indirect effects
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MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
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Multimodal Biological Knowledge Graph Completion via Triple Co-Attention Mechanism. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . 3928–3941
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Editing Large Language Models: Problems, Methods, and Opportunities
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Kai He, Rui Mao, Qika Lin, Yucheng Ruan, Xiang Lan, Mengling Feng, and Erik Cambria. 2023 · 2023
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Transformer-Patcher: One Mistake Worth One Neuron. In The Eleventh International Conference on Learning Representations
Zeyu Huang, Yikang Shen, Xiaofeng Zhang, Jie Zhou, Wenge Rong, and Zhang Xiong. 2023 · 2023
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Embracing Large Language Models for Medical Applications: Opportunities and Challenges
Mert Karabacak and Konstantinos Margetis. 2023 · 2023
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Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models
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Halueval: A large-scale hallucination evaluation benchmark for large language models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 6449–6464
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Faithful chain-of-thought reasoning
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Counterfactual Video Recommendation for Duration Debiasing. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 4894–4903
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Llama 2: Open Foundation and Fine-Tuned Chat Models
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Li Yunxiang, Li Zihan, Zhang Kai, Dan Ruilong, and Zhang You. 2023 · 2023
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Siren’s song in the AI ocean: a survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, et al · 2023
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A survey of large language models
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Can We Edit Factual Knowledge by In-Context Learning?. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, Singapore, 4862–4876
Ce Zheng, Lei Li, Qingxiu Dong, Yuxuan Fan, Zhiyong Wu, Jingjing Xu, and Baobao Chang. 2023 · 2023
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A survey of large language models in medicine: Progress, application, and challenge
Hongjian Zhou, Boyang Gu, Xinyu Zou, Yiru Li, Sam S Chen, Peilin Zhou, Junling Liu, Yining Hua, Chengfeng Mao, Xian Wu, et al · 2023
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A survey on evaluation of large language models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al · 2024
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AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) . 1346–1362
Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, and Huaxiu Yao. 2024 · 2024
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Contextual Distillation Model for Diversified Recommendation
Fan Li, Xu Si, Shisong Tang, Dingmin Wang, Kunyan Han, Bing Han, Guorui Zhou, Yang Song, and Hechang Chen. 2024 · 2024
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When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1104–1114
Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Derong Xu, Feng Tian, and Yefeng Zheng. 2024 · 2024
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Interpreting Key Mechanisms of Factual Recall in Transformer-Based Language Models
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A Comprehensive Study of Knowledge Editing for Large Language Models
Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, et al · 2024
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