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检索条件"机构=CAS Key Laboratory of AI Safety Institute of Computing Technology"
132 条 记 录,以下是31-40 订阅
排序:
Enhancing Training Data Attribution for Large Language Models with Fitting Error Consideration
Enhancing Training Data Attribution for Large Language Model...
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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024
作者: Wu, Kangxi Pang, Liang Shen, Huawei Cheng, Xueqi Key Laboratory of AI Safety Chinese Academy of Sciences Institute of Computing Technology CAS China University of Chinese Academy of Sciences China
The black-box nature of large language models (LLMs) poses challenges in interpreting results, impacting issues such as data intellectual property protection and hallucination tracing. Training data attribution (TDA) ... 详细信息
来源: 评论
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation  38
Understanding and Improving Adversarial Collaborative Filter...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Zhang, Kaike Cao, Qi Wu, Yunfan Sun, Fei Shen, Huawei Cheng, Xueqi CAS Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences Beijing China
Adversarial Collaborative Filtering (ACF), which typically applies adversarial perturbations at user and item embeddings through adversarial training, is widely recognized as an effective strategy for enhancing the ro...
来源: 评论
PKAD: Pretrained Knowledge is All You Need to Detect and Mitigate Textual Backdoor Attacks
PKAD: Pretrained Knowledge is All You Need to Detect and Mit...
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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024
作者: Chen, Yu Cao, Qi Zhang, Kaike Liu, Xuchao Shen, Huawei CAS Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences Beijing China
In textual backdoor attacks, attackers insert poisoned samples with triggered inputs and target labels into training datasets to manipulate model behavior, threatening the model's security and reliability. Current... 详细信息
来源: 评论
Augmentation-Aware Self-Supervision for Data-Efficient GAN Training  37
Augmentation-Aware Self-Supervision for Data-Efficient GAN T...
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37th Conference on Neural Information Processing Systems, NeurIPS 2023
作者: Hou, Liang Cao, Qi Yuan, Yige Zhao, Songtao Ma, Chongyang Pan, Siyuan Wan, Pengfei Wang, Zhongyuan Shen, Huawei Cheng, Xueqi CAS Key Laboratory of AI Safety and Security Institute of Computing Technology Chinese Academy of Sciences China CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Kuaishou Technology China
Training generative adversarial networks (GANs) with limited data is challenging because the discriminator is prone to overfitting. Previously proposed differentiable augmentation demonstrates improved data efficiency... 详细信息
来源: 评论
Qsnail: A Questionnaire Dataset for Sequential Question Generation  30
Qsnail: A Questionnaire Dataset for Sequential Question Gene...
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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024
作者: Lei, Yan Pang, Liang Wang, Yuanzhuo Shen, Huawei Cheng, Xueqi CAS Key Laboratory of AI Safety & Security Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
The questionnaire is a professional research methodology used for both qualitative and quantitative analysis of human opinions, preferences, attitudes, and behaviors. However, designing and evaluating questionnaires d... 详细信息
来源: 评论
Competition on robust deep learning
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National Science Review 2023年 第6期10卷 13-15页
作者: Yinpeng Dong Chang Liu Wenzhao Xiang Hang Su Jun Zhu Department of Computer Science and Technology Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Institute of Image Communication and Networks Engineering in the Department of Electronic Engineering (EE) Shanghai Jiao Tong University Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Peng Cheng Laboratory Pazhou Laboratory (Huangpu)
PROBLEM In recent years,the rapid development of artificial intelligence (ai) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,f... 详细信息
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Classifier Guidance Enhances Diffusion-Based Adversarial Purification by Preserving Predictive Information  27
Classifier Guidance Enhances Diffusion-Based Adversarial Pur...
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27th European Conference on Artificial Intelligence, ECai 2024
作者: Zhang, Mingkun Li, Jianing Chen, Wei Guo, Jiafeng Cheng, Xueqi CAS Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
Adversarial purification is one of the promising approaches to defend neural networks against adversarial attacks. Recently, methods utilizing diffusion probabilistic models have achieved great success for adversarial... 详细信息
来源: 评论
SLANG: New Concept Comprehension of Large Language Models
SLANG: New Concept Comprehension of Large Language Models
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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024
作者: Mei, Lingrui Liu, Shenghua Wang, Yiwei Bi, Baolong Cheng, Xueqi CAS Key Laboratory of AI Safety Institute of Computing Technology CAS China University of California Los Angeles United States University of California Merced United States University of Chinese Academy of Sciences China
The dynamic nature of language, particularly evident in the realm of slang and memes on the Internet, poses serious challenges to the adaptability of Large Language Models (LLMs). Traditionally anchored to static data... 详细信息
来源: 评论
Adaptive Token Biaser: Knowledge Editing via Biasing key Entities
Adaptive Token Biaser: Knowledge Editing via Biasing Key Ent...
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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024
作者: Bi, Baolong Liu, Shenghua Wang, Yiwei Mei, Lingrui Gao, Hongcheng Xu, Yilong Cheng, Xueqi CAS Key Laboratory of AI Safety Institute of Computing Technology CAS China University of Chinese Academy of Sciences China University of California Los Angeles United States University of California Merced United States
The parametric knowledge memorized by large language models (LLMs) becomes outdated quickly. In-context editing (ICE) is currently the most effective method for updating the knowledge of LLMs. Recent advancements invo... 详细信息
来源: 评论
List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation  24
List-aware Reranking-Truncation Joint Model for Search and R...
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33rd ACM Web Conference, WWW 2024
作者: Xu, Shicheng Pang, Liang Xu, Jun Shen, Huawei Cheng, Xueqi CAS Key Laboratory of AI Security Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China CAS Key Laboratory of AI Security Institute of Computing Technology Chinese Academy of Sciences Beijing China Gaoling School of Artificial Intelligence Renmin University of China Beijing China
The results of information retrieval (IR) are usually presented in the form of a ranking list of candidate documents, such as web search for humans and retrieval-augmented generation for large language models (LLMs). ... 详细信息
来源: 评论