MCIP: Protecting MCP Safety via Model Contextual Integrity Protocol

Privacy as contextual integrity

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Language models are few-shot learners

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Chatgpt evaluation on sentence level relations: A focus on temporal, causal, and discourse relations

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Chunkit Chan, Jiayang Cheng, Weiqi Wang, Yuxin Jiang, Tianqing Fang, Xin Liu, and Yangqiu Song. 2023 · 2023

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Attacking by aligning: Clean-label backdoor attacks on object detection

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Solving math word problems by combining language models with symbolic solvers

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Threat modeling methodology: Trike

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Toolformer: Language models can teach themselves to use tools

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Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023

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Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023

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Backdooring instruction-tuned large language models with virtual prompt injection

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Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen, Zheng Tang, Hai Wang, Vijay Srinivasan, Xiang Ren, and Hongxia Jin. 2023 · 2023

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Prompt as triggers for backdoor attack: Examining the vulnerability in language models

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Memorybank: Enhancing large language models with long-term memory

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Bathe: Defense against the jailbreak attack in multimodal large language models by treating harmful instruction as backdoor trigger

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Yulin Chen, Haoran Li, Yirui Zhang, Zihao Zheng, Yangqiu Song, and Bryan Hooi. 2024 · 2024

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Goldcoin: Grounding large language models in privacy laws via contextual integrity theory

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Wei Fan, Haoran Li, Zheye Deng, Weiqi Wang, and Yangqiu Song. 2024 · 2024

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Openrlhf: An easy-to-use, scalable and high-performance rlhf framework

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Jian Hu, Xibin Wu, Zilin Zhu, Xianyu, Weixun Wang, Dehao Zhang, and Yu Cao. 2024 · 2024

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Evaluating and enhancing llms agent based on theory of mind in guandan: A multi-player cooperative game under imperfect information

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How johnny can persuade llms to jailbreak them: Rethinking persuasion to challenge ai safety by humanizing llms

Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, and Weiyan Shi. 2024 · 2024

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Custom synthetic datasets

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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning

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DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, Xingkai Yu, Yu Wu, Z. F. Wu, Zhibin Gou, Zhihong Shao, Zhuoshu Li, Ziyi Gao, and 181 others. 2025 · 2025

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