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Kaixiong Zhou
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2020 – today
- 2024
- [c48]Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang:
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. ACL (1) 2024: 8069-8083 - [c47]Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong, Kaixiong Zhou, Ninghao Liu:
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answering. CIKM 2024: 2056-2066 - [c46]Jesus Barreda, Ashley Gomez, Ruben Puga, Kaixiong Zhou, Li Zhang:
COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification. CIKM 2024: 3622-3626 - [c45]Xin Juan, Kaixiong Zhou, Ninghao Liu, Tianlong Chen, Xin Wang:
Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision. CVPR 2024: 308-318 - [c44]Chuang Zhou, Junnan Dong, Xiao Huang, Zirui Liu, Kaixiong Zhou, Zhaozhuo Xu:
QUEST: Efficient Extreme Multi-Label Text Classification with Large Language Models on Commodity Hardware. EMNLP (Findings) 2024: 3929-3940 - [c43]Aditi Khandelwal, Harman Singh, Hengrui Gu, Tianlong Chen, Kaixiong Zhou:
Cross-Lingual Multi-Hop Knowledge Editing. EMNLP (Findings) 2024: 11995-12015 - [c42]Hengrui Gu, Kaixiong Zhou, Yili Wang, Ruobing Wang, Xin Wang:
Pioneering Reliable Assessment in Text-to-Image Knowledge Editing: Leveraging a Fine-Grained Dataset and an Innovative Criterion. EMNLP (Findings) 2024: 15303-15317 - [c41]Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang:
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. ICLR 2024 - [c40]Duy Le, Shaochen Zhong, Zirui Liu, Shuai Xu, Vipin Chaudhary, Kaixiong Zhou, Zhaozhuo Xu:
Knowledge Graphs Can be Learned with Just Intersection Features. ICML 2024 - [c39]Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang:
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. ICML 2024 - [c38]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
TVE: Learning Meta-attribution for Transferable Vision Explainer. ICML 2024 - [c37]Zhaozhuo Xu, Zirui Liu
, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Soft Prompt Recovers Compressed LLMs, Transferably. ICML 2024 - [c36]Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu:
GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024 - [c35]Xu Shen
Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models. KDD 2024: 2640-2650 - [i42]Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei:
Privacy-preserving Fine-tuning of Large Language Models through Flatness. CoRR abs/2403.04124 (2024) - [i41]Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong, Kaixiong Zhou, Ninghao Liu:
Retrieval-Enhanced Knowledge Editing for Multi-Hop Question Answering in Language Models. CoRR abs/2403.19631 (2024) - [i40]Xu Shen, Yili Wang, Kaixiong Zhou, Shirui Pan, Xin Wang:
Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models. CoRR abs/2404.15625 (2024) - [i39]Mingyu Jin, Haochen Xue, Zhenting Wang, Boming Kang, Ruosong Ye, Kaixiong Zhou, Mengnan Du, Yongfeng Zhang:
ProLLM: Protein Chain-of-Thoughts Enhanced LLM for Protein-Protein Interaction Prediction. CoRR abs/2405.06649 (2024) - [i38]Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang:
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. CoRR abs/2405.15564 (2024) - [i37]Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang:
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. CoRR abs/2406.13137 (2024) - [i36]Xinnan Zhang, Jialin Wu, Junyi Xie, Tianlong Chen, Kaixiong Zhou:
Benchmark on Drug Target Interaction Modeling from a Structure Perspective. CoRR abs/2407.04055 (2024) - [i35]Aditi Khandelwal, Harman Singh, Hengrui Gu, Tianlong Chen, Kaixiong Zhou:
Cross-Lingual Multi-Hop Knowledge Editing - Benchmarks, Analysis and a Simple Contrastive Learning based Approach. CoRR abs/2407.10275 (2024) - [i34]Jesus Barreda, Ashley Gomez, Ruben Puga, Kaixiong Zhou, Li Zhang:
COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification. CoRR abs/2409.09645 (2024) - 2023
- [j7]Tianlong Chen
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2769-2781 (2023) - [j6]Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi:
Adaptive RiskAware Bidding with Budget Constraint in Display Advertising. SIGKDD Explor. 25(1): 73-82 (2023) - [j5]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. SIGKDD Explor. 25(2): 4-13 (2023) - [j4]Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
DSpar: An Embarrassingly Simple Strategy for Efficient GNN training and inference via Degree-based Sparsification. Trans. Mach. Learn. Res. 2023 (2023) - [c34]Yu-Neng Chuang
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CIKM 2023: 5021-5025 - [c33]Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu:
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations. ICML 2023: 21951-21968 - [c32]Huiyuan Chen, Kaixiong Zhou, Zhimeng Jiang, Chin-Chia Michael Yeh, Xiaoting Li, Menghai Pan, Yan Zheng, Xia Hu, Hao Yang:
Probabilistic Masked Attention Networks for Explainable Sequential Recommendation. IJCAI 2023: 2068-2076 - [c31]Zirui Liu, Guanchu Wang, Shaochen (Henry) Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang (Ryan) Tang, Zhimeng Stephen Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. NeurIPS 2023 - [c30]Yucheng Shi, Kaixiong Zhou, Ninghao Liu:
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. ECML/PKDD (3) 2023: 104-121 - [c29]Huiyuan Chen
Hessian-aware Quantized Node Embeddings for Recommendation. RecSys 2023: 757-762 - [c28]Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. SDM 2023: 55-63 - [c27]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. SDM 2023: 676-684 - [i33]Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu:
A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges. CoRR abs/2303.07275 (2023) - [i32]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. CoRR abs/2304.07453 (2023) - [i31]Zhaozhuo Xu, Zirui Liu, Beidi Chen, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt. CoRR abs/2305.11186 (2023) - [i30]Zirui Liu, Guanchu Wang, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. CoRR abs/2305.15265 (2023) - [i29]Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Editable Graph Neural Network for Node Classifications. CoRR abs/2305.15529 (2023) - [i28]Yucheng Shi, Kaixiong Zhou, Ninghao Liu:
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. CoRR abs/2307.01053 (2023) - [i27]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang:
Hessian-aware Quantized Node Embeddings for Recommendation. CoRR abs/2309.01032 (2023) - [i26]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Ben Hu:
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CoRR abs/2309.01808 (2023) - [i25]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. CoRR abs/2310.14527 (2023) - [i24]Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang:
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. CoRR abs/2312.15194 (2023) - [i23]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
LETA: Learning Transferable Attribution for Generic Vision Explainer. CoRR abs/2312.15359 (2023) - 2022
- [j3]Kaixiong Zhou, Xiao Huang
Auto-GNN: Neural architecture search of graph neural networks. Frontiers Big Data 5 (2022) - [j2]Yuening Li
Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2365-2377 (2022) - [c26]Kai Guo
Orthogonal Graph Neural Networks. AAAI 2022: 3996-4004 - [c25]Duc N. M. Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks. AutoML 2022: 4/1-16 - [c24]Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang
AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training. CIKM 2022: 2046-2055 - [c23]Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
An Information Fusion Approach to Learning with Instance-Dependent Label Noise. ICLR 2022 - [c22]Zirui Liu
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression. ICLR 2022 - [c21]Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Table2Graph: Transforming Tabular Data to Unified Weighted Graph. IJCAI 2022: 2420-2426 - [c20]Mingchen Sun
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks. KDD 2022: 1717-1727 - [c19]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. NeurIPS 2022 - [c18]Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang:
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. RecSys 2022: 257-267 - [c17]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Towards Similarity-Aware Time-Series Classification. SDM 2022: 199-207 - [c16]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang:
Adversarial Graph Perturbations for Recommendations at Scale. SIGIR 2022: 1854-1858 - [i22]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Towards Similarity-Aware Time-Series Classification. CoRR abs/2201.01413 (2022) - [i21]Fan Yang, Qizhang Feng, Kaixiong Zhou, Jiahao Chen, Xia Hu:
Differentially Private Counterfactuals via Functional Mechanism. CoRR abs/2208.02878 (2022) - [i20]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. CoRR abs/2210.07494 (2022) - [i19]Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu:
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations. CoRR abs/2210.10737 (2022) - [i18]Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen, Xiao Huang
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks. CoRR abs/2211.07379 (2022) - [i17]Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang:
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. CoRR abs/2212.04540 (2022) - [i16]Cameron Diao, Kaixiong Zhou, Xiao Huang
MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning. CoRR abs/2212.10614 (2022) - [i15]Zhimeng Jiang
Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising. CoRR abs/2212.12533 (2022) - 2021
- [c15]Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu:
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. ICCV 2021: 4742-4750 - [c14]Yuening Li, Zhengzhang Chen
AutoOD: Neural Architecture Search for Outlier Detection. ICDE 2021: 2117-2122 - [c13]Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. NeurIPS 2021: 21834-21846 - [c12]Huachi Zhou
Temporal Augmented Graph Neural Networks for Session-Based Recommendations. SIGIR 2021: 1798-1802 - [i14]Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu:
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. CoRR abs/2103.14545 (2021) - [i13]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Simplifying Deep Reinforcement Learning via Self-Supervision. CoRR abs/2106.05526 (2021) - [i12]Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. CoRR abs/2107.02392 (2021) - [i11]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. CoRR abs/2108.10521 (2021) - [i10]Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. CoRR abs/2108.13555 (2021) - [i9]Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang:
Orthogonal Graph Neural Networks. CoRR abs/2109.11338 (2021) - [i8]Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang:
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. CoRR abs/2110.14855 (2021) - 2020
- [c11]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Neural Networks. IJCAI 2020: 1352-1358 - [c10]Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. KDD 2020: 461-471 - [c9]Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu:
Detecting Interactions from Neural Networks via Topological Analysis. NeurIPS 2020 - [c8]Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu:
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. NeurIPS 2020 - [c7]Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji
Deep Neural Networks with Knowledge Instillation. SDM 2020: 370-378 - [i7]Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu:
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. CoRR abs/2006.06972 (2020) - [i6]Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu:
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning. CoRR abs/2006.11321 (2020) - [i5]Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. CoRR abs/2006.15097 (2020) - [i4]Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu:
Towards Interaction Detection Using Topological Analysis on Neural Networks. CoRR abs/2010.13015 (2020)
2010 – 2019
- 2019
- [c6]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Experience Replay Optimization. IJCAI 2019: 4243-4249 - [i3]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Experience Replay Optimization. CoRR abs/1906.08387 (2019) - [i2]Kaixiong Zhou, Qingquan Song, Xiao Huang, Xia Hu:
Auto-GNN: Neural Architecture Search of Graph Neural Networks. CoRR abs/1909.03184 (2019) - [i1]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Convolutional Networks. CoRR abs/1912.08306 (2019) - 2017
- [j1]Kaixiong Zhou, Chen Gong, Nan Wu, Zhengyuan Xu:
Distributed Channel Allocation and Rate Control for Hybrid FSO/RF Vehicular Ad Hoc Networks. JOCN 9(8): 669-681 (2017) - [c5]Xin Huang, Kaixiong Zhou, Chao Xiang Shi, Jian Xin Chang, Meng Gao:
Transmissions and Network Management of Multiple 100 GB/s Based on Stacking Technology. ChinaCom (2) 2017: 102-111 - [c4]Mian Zeng, Kaixiong Zhou, Chen Gong, Shun Lou, Xianqing Jin, Zhengyuan Xu:
Design and demonstration of an indoor visible light communication network with dynamic user access and resource allocation. WCSP 2017: 1-6 - [c3]Kaixiong Zhou, Xin Huang, Chao Xiang Shi, Jian Xin Chang, Meng Gao:
Design and implementation of a novel 100G optical interface protocol converter. WCSP 2017: 1-4 - 2016
- [c2]Kaixiong Zhou, Chen Gong, Qian Gao, Zhengyuan Xu:
Inter-cell interference coordination for multi-color visible light communication networks. GlobalSIP 2016: 6-10 - 2015
- [c1]Kaixiong Zhou, Lin Zhang, Ming Jiang:
Enhanced effective SNR prediction for LTE downlink. ICCC 2015: 1-6
Coauthor Index
[c38] [c37] [c36] [j7] [j6] [j4] [c34] [c33] [c32] [c31] [c29] [c28] [c27] [i32] [i31] [i30] [i29] [i27] [i26] [i23] [j3] [j2] [c26] [c25] [c23] [c22] [c21] [c19] [c18] [c17] [c16] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [c15] [c14] [c13] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [c11] [c10] [c9] [c8] [c7] [i7] [i6] [i5] [i4] [c6] [i3] [i2] [i1]
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