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Large language models (LLMs) have transformed the development of embodied intelligence.
California vehicle code 23113, 2000
Casetext · 2000
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Embodied intelligence
Angelo Cangelosi, Josh Bongard, Martin H Fischer, and Stefano Nolfi · 2015
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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A corpus of natural language for visual reasoning
Alane Suhr, Mike Lewis, James Yeh, and Yoav Artzi · 2017
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Transferable adversarial attacks for image and video object detection
Xingxing Wei, Siyuan Liang, Ning Chen, and Xiaochun Cao · 2018
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Trojaning attack on neural networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2018
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Machine learning and security: Protecting systems with data and algorithms
Clarence Chio and David Freeman · 2018
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Virtualhome: Simulating household activities via programs
Xavier Puig, Kevin Ra, Marko Boben, Jiaman Li, Tingwu Wang, Sanja Fidler, and Antonio Torralba · 2018
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Taku Kudo and John Richardson · 2018
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 2019
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Perceptual-sensitive gan for generating adversarial patches
Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, and Dacheng Tao · 2019
Earlier work this paper cites.
Latent backdoor attacks on deep neural networks
Yuanshun Yao, Huiying Li, Haitao Zheng, and Ben Y Zhao · 2019
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Embodied intelligence weaves a better future
Dongdong Jin and Li Zhang · 2020
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Efficient adversarial attacks for visual object tracking
Siyuan Liang, Xingxing Wei, Siyuan Yao, and Xiaochun Cao · 2020
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Input-aware dynamic backdoor attack
Tuan Anh Nguyen and Anh Tran · 2020
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J Davison · 2020
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End-to-end autonomous driving risk analysis: A behavioural anomaly detection approach
Cian Ryan, Finbarr Murphy, and Martin Mullins · 2020
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Bias-based universal adversarial patch attack for automatic check-out
Aishan Liu, Jiakai Wang, Xianglong Liu, Bowen Cao, Chongzhi Zhang, and Hang Yu · 2020
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Embodied intelligence via learning and evolution
Agrim Gupta, Silvio Savarese, Surya Ganguli, and Li Fei-Fei · 2021
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Generate more imperceptible adversarial examples for object detection
Siyuan Liang, Xingxing Wei, and Xiaochun Cao · 2021
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You autocomplete me: Poisoning vulnerabilities in neural code completion
Roei Schuster, Congzheng Song, Eran Tromer, and Vitaly Shmatikov · 2021
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Dirty road can attack: Security of deep learning based automated lane centering under physical-world attack
Takami Sato, Junjie Shen, Ningfei Wang, Yunhan Jia, Xue Lin, and Qi Alfred Chen · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Onion: A simple and effective defense against textual backdoor attacks
Fanchao Qi, Yangyi Chen, Mukai Li, Yuan Yao, Zhiyuan Liu, and Maosong Sun · 2021
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Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant · 2021
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Pbdt: Python backdoor detection model based on combined features
Yong Fang, Mingyu Xie, and Cheng Huang · 2021
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Training robust deep neural networks via adversarial noise propagation
Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, and Dacheng Tao · 2021
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Interpreting and improving adversarial robustness of deep neural networks with neuron sensitivity
Chongzhi Zhang, Aishan Liu, Xianglong Liu, Yitao Xu, Hang Yu, Yuqing Ma, and Tianlin Li · 2021
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Dual attention suppression attack: Generate adversarial camouflage in physical world
Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, and Xianglong Liu · 2021
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Yue Wang, Weishi Wang, Shafiq Joty, and Steven CH Hoi · 2021
Cited alongside, same era.
Parallel rectangle flip attack: A query-based black-box attack against object detection
Siyuan Liang, Baoyuan Wu, Yanbo Fan, Xingxing Wei, and Xiaochun Cao · 2022
Cited alongside, same era.
A large-scale multiple-objective method for black-box attack against object detection
Siyuan Liang, Longkang Li, Yanbo Fan, Xiaojun Jia, Jingzhi Li, Baoyuan Wu, and Xiaochun Cao · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Universal watermark vaccine: Universal adversarial perturbations for watermark protection
Jianbo Chen, Xinwei Liu, Siyuan Liang, Xiaojun Jia, and Yuan Xun · 2023
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Privacy-enhancing face obfuscation guided by semantic-aware attribution maps
Privacy enhancing face obfuscation guided by semantic-aware attribution maps · 2023
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Isolation and induction: Training robust deep neural networks against model stealing attacks
Jun Guo, Xingyu Zheng, Aishan Liu, Siyuan Liang, Yisong Xiao, Yichao Wu, and Xianglong Liu · 2023
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Face encryption via frequency-restricted identity-agnostic attacks
Xin Dong, Rui Wang, Siyuan Liang, Aishan Liu, and Lihua Jing · 2023
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Unified demonstration retriever for in-context learning
Xiaonan Li, Kai Lv, Hang Yan, Tianyang Lin, Wei Zhu, Yuan Ni, Guotong Xie, Xiaoling Wang, and Xipeng Qiu · 2023
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Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, and Zhifang Sui · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Imitated detectors: Stealing knowledge of black-box object detectors
Siyuan Liang, Aishan Liu, Jiawei Liang, Longkang Li, Yang Bai, and Xiaochun Cao · 2022
Cited alongside, same era.
Universal backdoor attacks detection via adaptive adversarial probe
Yuhang Wang, Huafeng Shi, Rui Min, Ruijia Wu, Siyuan Liang, Yichao Wu, Ding Liang, and Aishan Liu · 2022
Cited alongside, same era.
Gps: Genetic prompt search for efficient few-shot learning
Hanwei Xu, Yujun Chen, Yulun Du, Nan Shao, Yanggang Wang, Haiyu Li, and Zhilin Yang · 2022
Cited alongside, same era.
Backdoors in neural models of source code
Goutham Ramakrishnan and Aws Albarghouthi · 2022
Cited alongside, same era.
Chatgpt, 2023
OpenAI · 2023
Cited alongside, same era.
Large language models for code: Security hardening and adversarial testing
Jingxuan He and Martin Vechev · 2023
Later among the works it cites.
Improving robust fairness via balance adversarial training
Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, Xianglong Liu, and Aishan Liu · 2023
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Exploring the relationship between architectural design and adversarially robust generalization
Aishan Liu, Shiyu Tang, Siyuan Liang, Ruihao Gong, Boxi Wu, Xianglong Liu, and Dacheng Tao · 2023
Later among the works it cites.
Exploring inconsistent knowledge distillation for object detection with data augmentation
Jiawei Liang, Siyuan Liang, Aishan Liu, Ke Ma, Jingzhi Li, and Xiaochun Cao · 2023
Later among the works it cites.
Towards defending multiple lp-norm bounded adversarial perturbations via gated batch normalization
Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, and Dacheng Tao · 2023
Later among the works it cites.
A comprehensive evaluation framework for deep model robustness
Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu, Jian Dong, Xianglong Liu, and Wenjun Wu · 2023
Later among the works it cites.
Poster: Fooling xai with explanation-aware backdoors
Maximilian Noppel and Christian Wressnegger · 2023
Later among the works it cites.
Narcissus: A practical clean-label backdoor attack with limited information
Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, and Ruoxi Jia · 2023
Later among the works it cites.
Hide in thicket: Generating imperceptible and rational adversarial perturbations on 3d point clouds
Tianrui Lou, Xiaojun Jia, Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, and Xiaochun Cao · 2024
Closest in time.
Environmental matching attack against unmanned aerial vehicles object detection
Dehong Kong, Siyuan Liang, and Wenqi Ren · 2024
Closest in time.
Badclip: Dual-embedding guided backdoor attack on multimodal contrastive learning, 2024
Siyuan Liang, Mingli Zhu, Aishan Liu, Baoyuan Wu, Xiaochun Cao, and Ee-Chien Chang · 2024
Closest in time.
Poisoned forgery face: Towards backdoor attacks on face forgery detection
Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, and Xiaochun Cao · 2024
Closest in time.
Vl-trojan: Multimodal instruction backdoor attacks against autoregressive visual language models
Jiawei Liang, Siyuan Liang, Man Luo, Aishan Liu, Dongchen Han, Ee-Chien Chang, and Xiaochun Cao · 2024
Closest in time.
Towards robust physical-world backdoor attacks on lane detection
Xinwei Zhang, Aishan Liu, Tianyuan Zhang, Siyuan Liang, and Xianglong Liu · 2024
Closest in time.
Breaking the false sense of security in backdoor defense through re-activation attack
Mingli Zhu, Siyuan Liang, and Baoyuan Wu · 2024
Closest in time.
Revisiting backdoor attacks against large vision-language models
Siyuan Liang, Jiawei Liang, Tianyu Pang, Chao Du, Aishan Liu, Ee-Chien Chang, and Xiaochun Cao · 2024
Closest in time.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2024
Closest in time.
Universal vulnerabilities in large language models: Backdoor attacks for in-context learning
Shuai Zhao, Meihuizi Jia, Luu Anh Tuan, Fengjun Pan, and Jinming Wen · 2024
Closest in time.
Coercing llms to do and reveal (almost) anything
Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, and Tom Goldstein · 2024
Closest in time.
https://www.pixmoving.com/pixloop
Pixloop, 2024 · 2024
Closest in time.
https://www.pixmoving.com/about-us
Who we are, 2024 · 2024
Closest in time.
Multimodal unlearnable examples: Protecting data against multimodal contrastive learning
Xinwei Liu, Xiaojun Jia, Yuan Xun, Siyuan Liang, and Xiaochun Cao · 2024
Closest in time.
Siyuan Liang, Kuanrong Liu, Jiajun Gong, Jiawei Liang, Yuan Xun, Ee-Chien Chang, and Xiaochun Cao · 2024
Closest in time.
Stealthy backdoor attack for code models
Zhou Yang, Bowen Xu, Jie M Zhang, Hong Jin Kang, Jieke Shi, Junda He, and David Lo · 2024
Closest in time.
Lanevil: Benchmarking the robustness of lane detection to environmental illusions
Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu, Xianglong Liu, and Dacheng Tao · 2024
Closest in time.