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2020 – today
- 2024
[j3]Jingfeng Yang
, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Shaochen Zhong, Bing Yin, Xia Ben Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. ACM Trans. Knowl. Discov. Data 18(6): 160:1-160:32 (2024)- [c42]Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao Cheng, Tuo Zhao, Jing Gao:
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. EMNLP 2024: 1009-1025 - [c41]Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang:
Data Diversity Matters for Robust Instruction Tuning. EMNLP (Findings) 2024: 3411-3425 - [c40]Fenglin Liu, Zheng Li, Hongjian Zhou, Qingyu Yin, Jingfeng Yang, Xianfeng Tang, Chen Luo, Ming Zeng, Haoming Jiang, Yifan Gao, Priyanka Nigam, Sreyashi Nag, Bing Yin, Yining Hua, Xuan Zhou, Omid Rohanian, Anshul Thakur, Lei A. Clifton, David A. Clifton:
Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark. EMNLP 2024: 13696-13710 - [c39]Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian J. McAuley:
MEMORYLLM: Towards Self-Updatable Large Language Models. ICML 2024 - [i41]Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao:
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR abs/2406.02764 (2024) - [i40]Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao:
Robust Reinforcement Learning from Corrupted Human Feedback. CoRR abs/2406.15568 (2024) - [i39]Zongyue Qin, Chen Luo, Zhengyang Wang, Haoming Jiang, Yizhou Sun:
Relational Database Augmented Large Language Model. CoRR abs/2407.15071 (2024) - [i38]Kewei Cheng, Jingfeng Yang, Haoming Jiang, Zhengyang Wang, Binxuan Huang, Ruirui Li, Shiyang Li, Zheng Li, Yifan Gao, Xian Li, Bing Yin, Yizhou Sun:
Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs. CoRR abs/2408.00114 (2024) - [i37]Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li:
RNR: Teaching Large Language Models to Follow Roles and Rules. CoRR abs/2409.13733 (2024) - 2023
- [c38]Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao:
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. ACL (industry) 2023: 616-628 - [c37]Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin:
Graph Reasoning for Question Answering with Triplet Retrieval. ACL (Findings) 2023: 3366-3375 - [c36]Karan Samel, Houyu Zhang, Jun Ma, Haoming Jiang, Qing Ping, Sheng Wang, Yi Xu, Belinda Zeng, Trishul Chilimbi:
SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce. IEEE Big Data 2023: 838-846 - [c35]Hui Liu, Qingyu Yin, Zhengyang Wang, Chenwei Zhang, Haoming Jiang, Yifan Gao, Zheng Li, Xian Li, Chao Zhang, Bing Yin, William Wang, Xiaodan Zhu:
Knowledge-Selective Pretraining for Attribute Value Extraction. EMNLP (Findings) 2023: 8062-8074 - [c34]Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao:
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. ICLR 2023 - [c33]Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha:
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. ICML 2023: 20210-20220 - [c32]Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao:
LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. KDD 2023: 2302-2313 - [c31]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS 2023 - [i36]Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao:
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR abs/2302.09632 (2023) - [i35]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. CoRR abs/2304.13712 (2023) - [i34]Jie Huang, Yifan Gao, Zheng Li, Jingfeng Yang, Yangqiu Song, Chao Zhang, Zining Zhu, Haoming Jiang, Kevin Chen-Chuan Chang, Bing Yin:
CCGen: Explainable Complementary Concept Generation in E-Commerce. CoRR abs/2305.11480 (2023) - [i33]Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, Bing Yin:
Graph Reasoning for Question Answering with Triplet Retrieval. CoRR abs/2305.18742 (2023) - [i32]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR abs/2307.09688 (2023) - [i31]Zining Zhu, Haoming Jiang, Jingfeng Yang, Sreyashi Nag, Chao Zhang, Jie Huang, Yifan Gao, Frank Rudzicz, Bing Yin:
Situated Natural Language Explanations. CoRR abs/2308.14115 (2023) - [i30]Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha:
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. CoRR abs/2310.16336 (2023) - 2022
- [c30]Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang:
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. ACL (1) 2022: 474-485 - [c29]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. ICLR 2022 - [c28]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin:
Condensing Graphs via One-Step Gradient Matching. KDD 2022: 720-730 - [c27]Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang:
AutoGDA: Automated Graph Data Augmentation for Node Classification. LoG 2022: 32 - [c26]Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang:
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models. NAACL-HLT (Findings) 2022: 49-60 - [c25]Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha:
Self-Training with Differentiable Teacher. NAACL-HLT (Findings) 2022: 933-949 - [c24]Chen Luo, William Headden, Neela Avudaiappan, Haoming Jiang, Tianyu Cao, Qingyu Yin, Yifan Gao, Zheng Li, Rahul Goutam, Haiyang Zhang, Bing Yin:
Query Attribute Recommendation at Amazon Search. RecSys 2022: 506-508 - [i29]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR abs/2202.02664 (2022) - [i28]Zijie Huang, Zheng Li, Haoming Jiang, Tianyu Cao, Hanqing Lu, Bing Yin, Karthik Subbian, Yizhou Sun, Wei Wang:
Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment. CoRR abs/2203.14987 (2022) - [i27]Jingfeng Yang, Haoming Jiang, Qingyu Yin, Danqing Zhang, Bing Yin, Diyi Yang:
SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models. CoRR abs/2205.07381 (2022) - [i26]Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying:
Condensing Graphs via One-Step Gradient Matching. CoRR abs/2206.07746 (2022) - [i25]Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao:
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR abs/2209.07499 (2022) - [i24]Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao:
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. CoRR abs/2209.07584 (2022) - [i23]Haoming Jiang, Tianyu Cao, Zheng Li, Chen Luo, Xianfeng Tang, Qingyu Yin, Danqing Zhang, Rahul Goutam, Bing Yin:
Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding. CoRR abs/2210.03915 (2022) - 2021
- [b1]Haoming Jiang:
Reducing Human Labor Cost in Deep Learning for Natural Language Processing. Georgia Institute of Technology, Atlanta, GA, USA, 2021 - [c23]Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao:
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. ACL/IJCNLP (1) 2021: 1775-1789 - [c22]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) 2021: 6524-6538 - [c21]Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao:
Learning to Defend by Learning to Attack. AISTATS 2021: 577-585 - [c20]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. EMNLP (Findings) 2021: 3658-3670 - [c19]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. EMNLP (Findings) 2021: 4118-4131 - [c18]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. EMNLP (1) 2021: 6562-6577 - [c17]Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei:
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) 2021: 7419-7451 - [c16]Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang:
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. NAACL-HLT 2021: 1063-1077 - [i22]Haoming Jiang, Bo Dai, Mengjiao Yang, Wei Wei, Tuo Zhao:
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. CoRR abs/2102.10242 (2021) - [i21]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. CoRR abs/2103.11088 (2021) - [i20]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. CoRR abs/2104.04886 (2021) - [i19]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR abs/2105.12002 (2021) - [i18]Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao:
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. CoRR abs/2106.08977 (2021) - [i17]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. CoRR abs/2109.07048 (2021) - [i16]Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha:
Self-Training with Differentiable Teacher. CoRR abs/2109.07049 (2021) - 2020
- [c15]Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao:
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. ACL 2020: 1823-1834 - [c14]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. ACL 2020: 2177-2190 - [c13]Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang:
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. EMNLP (1) 2020: 1326-1340 - [c12]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. ICLR 2020 - [c11]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Robust and Smooth Policy. ICML 2020: 8707-8718 - [c10]Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha:
Transformer Hawkes Process. ICML 2020: 11692-11702 - [c9]Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. KDD 2020: 1054-1064 - [i15]Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha:
Transformer Hawkes Process. CoRR abs/2002.09291 (2020) - [i14]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Smooth Policy. CoRR abs/2003.09534 (2020) - [i13]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR abs/2006.15261 (2020) - [i12]Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. CoRR abs/2006.15509 (2020) - [i11]Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang:
Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. CoRR abs/2010.07835 (2020) - [i10]Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang:
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. CoRR abs/2010.11506 (2020)
2010 – 2019
- 2019
- [j2]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. 20: 44:1-44:5 (2019) - [j1]Xuejin Chen, Haoming Jiang, Tingting Xuan, Lihan Huang, Ligang Liu:
Designing deployable 3D scissor structures with ball-and-socket joints. Comput. Animat. Virtual Worlds 30(1) (2019) - [c8]Yifu Sun, Haoming Jiang:
Contextual Text Denoising with Masked Language Model. W-NUT@EMNLP 2019: 286-290 - [c7]Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao:
Learning to Defense by Learning to Attack. DGS@ICLR 2019 - [c6]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. ICLR (Poster) 2019 - [c5]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. DGS@ICLR 2019 - [c4]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. ICML 2019: 6882-6892 - [c3]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. NeurIPS 2019: 8172-8182 - [c2]Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha:
Meta Learning with Relational Information for Short Sequences. NeurIPS 2019: 9901-9912 - [c1]Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI 2019: 49-59 - [i9]Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha:
On Scalable and Efficient Computation of Large Scale Optimal Transport. CoRR abs/1905.00158 (2019) - [i8]Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao:
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. CoRR abs/1908.01842 (2019) - [i7]Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han:
On the Variance of the Adaptive Learning Rate and Beyond. CoRR abs/1908.03265 (2019) - [i6]Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha:
Meta Learning with Relational Information for Short Sequences. CoRR abs/1909.02105 (2019) - [i5]Yifu Sun, Haoming Jiang:
Contextual Text Denoising with Masked Language Models. CoRR abs/1910.14080 (2019) - [i4]Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao:
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. CoRR abs/1911.02692 (2019) - [i3]Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao:
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. CoRR abs/1911.03437 (2019) - 2018
- [i2]Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao:
Learning to Defense by Learning to Attack. CoRR abs/1811.01213 (2018) - [i1]Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao:
On Computation and Generalization of GANs with Spectrum Control. CoRR abs/1812.10912 (2018)
Coauthor Index
[c42] [c41] [i41] [i40] [i37] [c38] [c34] [c33] [c32] [i36] [i30] [c29] [c25] [i29] [i25] [i24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [c15] [c14] [c13] [c11] [c10] [c9] [i15] [i14] [i13] [i12] [i11] [i10] [j2] [c7] [c6] [c5] [c4] [c3] [c2] [c1] [i9] [i8] [i6] [i4] [i3] [i2] [i1]
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