default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKun Gai
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c79]Lei Lin, Jia-Yi Fu, Pengli Liu, Qingyang Li, Yan Gong, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai:
Just Ask One More Time! Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios. ACL (Findings) 2024: 3829-3852- [c78]Yuchong Sun, Che Liu, Kun Zhou, Jinwen Huang, Ruihua Song, Xin Zhao, Fuzheng Zhang, Di Zhang, Kun Gai:
Parrot: Enhancing Multi-Turn Instruction Following for Large Language Models. ACL (1) 2024: 9729-9750 - [c77]Gaode Chen, Yuezihan Jiang, Rui Huang, Kuo Cai, Yunze Luo, Ruina Sun, Qi Zhang, Han Li, Kun Gai:
Missing Interest Modeling with Lifelong User Behavior Data for Retrieval Recommendation. CIKM 2024: 4390-4396 - [c76]Zhiqiang Liu, Xiaoxiao Xu, Jiaqi Yu, Han Xu, Lantao Hu, Han Li, Kun Gai:
A Self-Adaptive Fairness Constraint Framework for Industrial Recommender System. CIKM 2024: 4726-4733 - [c75]Zihua Si, Lin Guan, Zhongxiang Sun, Xiaoxue Zang, Jing Lu, Yiqun Hui, Xingchao Cao, Zeyu Yang, Yichen Zheng, Dewei Leng, Kai Zheng, Chenbin Zhang, Yanan Niu, Yang Song, Kun Gai:
TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou. CIKM 2024: 4890-4897 - [c74]Chenxi Sun, Hongzhi Zhang, Zijia Lin, Jingyuan Zhang, Fuzheng Zhang, Zhongyuan Wang, Bin Chen, Chengru Song, Di Zhang, Kun Gai, Deyi Xiong:
Decoding at the Speed of Thought: Harnessing Parallel Decoding of Lexical Units for LLMs. LREC/COLING 2024: 4476-4487 - [c73]Xiaoxue Cheng, Junyi Li, Xin Zhao, Hongzhi Zhang, Fuzheng Zhang, Di Zhang, Kun Gai, Ji-Rong Wen:
Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector. EMNLP 2024: 14600-14615 - [c72]Jiao Ou, Jiayu Wu, Che Liu, Fuzheng Zhang, Di Zhang, Kun Gai:
Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues. EMNLP 2024: 17402-17431 - [c71]Yang Jin, Kun Xu, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin Chen, Chengru Song, Dai Meng, Di Zhang, Wenwu Ou, Kun Gai, Yadong Mu:
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization. ICLR 2024 - [c70]Yang Jin, Zhicheng Sun, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Quzhe Huang, Chengru Song, Yuliang Liu, Di Zhang, Yang Song, Kun Gai, Yadong Mu:
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization. ICML 2024 - [c69]Xiaobei Wang
, Shuchang Liu, Xueliang Wang, Qingpeng Cai, Lantao Hu, Han Li, Peng Jiang, Kun Gai, Guangming Xie:
Future Impact Decomposition in Request-level Recommendations. KDD 2024: 5905-5916 - [c68]Yuting Zhang, Zhao Zhang, Yiqing Wu, Ying Sun, Fuzhen Zhuang, Wenhui Yu, Lantao Hu, Han Li, Kun Gai, Zhulin An, Yongjun Xu:
Tag Tree-Guided Multi-grained Alignment for Multi-Domain Short Video Recommendation. ACM Multimedia 2024: 5683-5691 - [c67]Jiao Ou, Junda Lu, Che Liu, Yihong Tang, Fuzheng Zhang, Di Zhang, Kun Gai:
DialogBench: Evaluating LLMs as Human-like Dialogue Systems. NAACL-HLT 2024: 6137-6170 - [c66]Gaode Chen, Ruina Sun, Yuezihan Jiang, Jiangxia Cao, Qi Zhang, Jingjian Lin, Han Li, Kun Gai, Xinghua Zhang:
A Multi-modal Modeling Framework for Cold-start Short-video Recommendation. RecSys 2024: 391-400 - [c65]Shuo Su, Xiaoshuang Chen, Yao Wang, Yulin Wu, Ziqiang Zhang, Kaiqiao Zhan, Ben Wang, Kun Gai:
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems. RecSys 2024: 670-679 - [c64]Zijian Zhang, Shuchang Liu, Jiaao Yu, Qingpeng Cai, Xiangyu Zhao, Chunxu Zhang, Ziru Liu, Qidong Liu, Hongwei Zhao, Lantao Hu, Peng Jiang, Kun Gai:
M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework. SIGIR 2024: 893-902 - [c63]Nian Li, Xin Ban, Cheng Ling, Chen Gao, Lantao Hu, Peng Jiang, Kun Gai, Yong Li, Qingmin Liao:
Modeling User Fatigue for Sequential Recommendation. SIGIR 2024: 996-1005 - [c62]Ziru Liu, Shuchang Liu, Zijian Zhang, Qingpeng Cai, Xiangyu Zhao, Kesen Zhao, Lantao Hu, Peng Jiang, Kun Gai:
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention. SIGIR 2024: 1872-1882 - [c61]Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li:
Inverse Learning with Extremely Sparse Feedback for Recommendation. WSDM 2024: 396-404 - [c60]Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang:
Mixed Attention Network for Cross-domain Sequential Recommendation. WSDM 2024: 405-413 - [c59]Xiaoxiao Xu, Hao Wu, Wenhui Yu, Lantao Hu, Peng Jiang, Kun Gai:
Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples. WWW (Companion Volume) 2024: 453-460 - [c58]Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai:
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. WWW 2024: 3621-3631 - [c57]Cheng Wu, Shaoyun Shi, Chaokun Wang, Ziyang Liu, Wang Peng, Wenjin Wu, Dongying Kong, Han Li, Kun Gai:
Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework. WWW 2024: 3756-3766 - [c56]Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai:
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems. WWW 2024: 3798-3809 - [i77]Yang Jin, Zhicheng Sun, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Quzhe Huang, Chengru Song, Yuliang Liu, Di Zhang, Yang Song, Kun Gai, Yadong Mu:
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization. CoRR abs/2402.03161 (2024) - [i76]Ziru Liu, Shuchang Liu, Zijian Zhang, Qingpeng Cai, Xiangyu Zhao, Kesen Zhao, Lantao Hu, Peng Jiang, Kun Gai:
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention. CoRR abs/2404.03637 (2024) - [i75]Yabin Zhang, Wenhui Yu, Erhan Zhang, Xu Chen, Lantao Hu, Peng Jiang, Kun Gai:
RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm. CoRR abs/2404.08675 (2024) - [i74]Jiao Ou, Jiayu Wu, Che Liu, Fuzheng Zhang, Di Zhang, Kun Gai:
Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues. CoRR abs/2404.11095 (2024) - [i73]Zijian Zhang, Shuchang Liu, Jiaao Yu, Qingpeng Cai, Xiangyu Zhao, Chunxu Zhang, Ziru Liu, Qidong Liu, Hongwei Zhao, Lantao Hu, Peng Jiang, Kun Gai:
M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework. CoRR abs/2404.18465 (2024) - [i72]Jian Jia, Yipei Wang, Yan Li, Honggang Chen, Xuehan Bai, Zhaocheng Liu, Jian Liang, Quan Chen, Han Li, Peng Jiang, Kun Gai:
Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application. CoRR abs/2405.03988 (2024) - [i71]Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai:
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. CoRR abs/2405.04844 (2024) - [i70]Nian Li, Xin Ban, Cheng Ling, Chen Gao, Lantao Hu, Peng Jiang, Kun Gai, Yong Li, Qingmin Liao:
Modeling User Fatigue for Sequential Recommendation. CoRR abs/2405.11764 (2024) - [i69]Zhicheng Sun, Zhenhao Yang, Yang Jin, Haozhe Chi, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Di Zhang, Yang Song, Kun Gai, Yadong Mu:
RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance. CoRR abs/2405.14677 (2024) - [i68]Chenxi Sun, Hongzhi Zhang, Zijia Lin, Jingyuan Zhang, Fuzheng Zhang, Zhongyuan Wang, Bin Chen, Chengru Song, Di Zhang, Kun Gai, Deyi Xiong:
Decoding at the Speed of Thought: Harnessing Parallel Decoding of Lexical Units for LLMs. CoRR abs/2405.15208 (2024) - [i67]Xiaoxue Cheng, Junyi Li, Wayne Xin Zhao, Hongzhi Zhang, Fuzheng Zhang, Di Zhang, Kun Gai, Ji-Rong Wen:
Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector. CoRR abs/2406.11277 (2024) - [i66]Zhongxiang Fan, Zhaocheng Liu, Jian Liang, Dongying Kong, Han Li, Peng Jiang, Shuang Li, Kun Gai:
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction. CoRR abs/2407.01607 (2024) - [i65]Zihua Si, Lin Guan, Zhongxiang Sun, Xiaoxue Zang, Jing Lu, Yiqun Hui, Xingchao Cao, Zeyu Yang, Yichen Zheng, Dewei Leng, Kai Zheng, Chenbin Zhang, Yanan Niu, Yang Song, Kun Gai:
TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou. CoRR abs/2407.16357 (2024) - [i64]Xu Wang, Jiangxia Cao, Zhiyi Fu, Kun Gai, Guorui Zhou:
HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou. CoRR abs/2408.05430 (2024) - [i63]Shuo Su, Xiaoshuang Chen, Yao Wang, Yulin Wu, Ziqiang Zhang, Kaiqiao Zhan, Ben Wang, Kun Gai:
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems. CoRR abs/2409.13175 (2024) - [i62]Yihong Tang, Jiao Ou, Che Liu, Fuzheng Zhang, Di Zhang, Kun Gai:
ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning. CoRR abs/2409.14710 (2024) - 2023
- [c55]Wanqi Xue, Qingpeng Cai, Ruohan Zhan, Dong Zheng, Peng Jiang, Kun Gai, Bo An:
ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor. ICLR 2023 - [c54]Yabin Zhang, Weiqi Shao, Xu Chen, Yali Du, Xiaoxiao Xu, Dong Zheng, Changhua Pei, Shuai Zhang, Peng Jiang, Kun Gai:
A Multi-Agent Framework for Recommendation with Heterogeneous Sources. IJCNN 2023: 1-8 - [c53]Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai:
Generative Flow Network for Listwise Recommendation. KDD 2023: 1524-1534 - [c52]Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai:
Graph Contrastive Learning with Generative Adversarial Network. KDD 2023: 2721-2730 - [c51]Wanqi Xue, Qingpeng Cai, Zhenghai Xue, Shuo Sun, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An:
PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement. KDD 2023: 2874-2884 - [c50]Jianxin Chang, Chenbin Zhang, Zhiyi Fu, Xiaoxue Zang, Lin Guan, Jing Lu, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai:
TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou. KDD 2023: 3785-3794 - [c49]Jianxin Chang, Chenbin Zhang, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai:
PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information. KDD 2023: 3795-3804 - [c48]Zhenghai Xue, Qingpeng Cai, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An:
State Regularized Policy Optimization on Data with Dynamics Shift. NeurIPS 2023 - [c47]Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai:
KuaiSim: A Comprehensive Simulator for Recommender Systems. NeurIPS 2023 - [c46]Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Depeng Jin, Yong Li:
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation. RecSys 2023: 540-550 - [c45]Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou, Kun Gai:
Multi-behavior Self-supervised Learning for Recommendation. SIGIR 2023: 496-505 - [c44]Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai, Ji-Rong Wen:
When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation. SIGIR 2023: 1313-1323 - [c43]Yuan Zhang, Xue Dong, Weijie Ding, Biao Li, Peng Jiang, Kun Gai:
Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems from a Multi-task Perspective. WWW (Companion Volume) 2023: 366-370 - [c42]Weiqi Zhao, Dian Tang, Xin Chen, Dawei Lv, Daoli Ou, Biao Li, Peng Jiang, Kun Gai:
Disentangled Causal Embedding With Contrastive Learning For Recommender System. WWW (Companion Volume) 2023: 406-410 - [c41]Qingpeng Cai, Shuchang Liu, Xueliang Wang, Tianyou Zuo, Wentao Xie, Bin Yang, Dong Zheng, Peng Jiang, Kun Gai:
Reinforcing User Retention in a Billion Scale Short Video Recommender System. WWW (Companion Volume) 2023: 421-426 - [c40]Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Peng Jiang, Kun Gai, Xiangyu Zhao, Yongfeng Zhang:
Exploration and Regularization of the Latent Action Space in Recommendation. WWW 2023: 833-844 - [c39]Qingpeng Cai, Zhenghai Xue, Chi Zhang, Wanqi Xue, Shuchang Liu, Ruohan Zhan, Xueliang Wang, Tianyou Zuo, Wentao Xie, Dong Zheng, Peng Jiang, Kun Gai:
Two-Stage Constrained Actor-Critic for Short Video Recommendation. WWW 2023: 865-875 - [c38]Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang, Kun Gai:
Multi-Task Recommendations with Reinforcement Learning. WWW 2023: 1273-1282 - [i61]Jianxin Chang, Chenbin Zhang, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai:
PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information. CoRR abs/2302.01115 (2023) - [i60]Qingpeng Cai, Zhenghai Xue, Chi Zhang, Wanqi Xue, Shuchang Liu, Ruohan Zhan, Xueliang Wang, Tianyou Zuo, Wentao Xie, Dong Zheng, Peng Jiang, Kun Gai:
Two-Stage Constrained Actor-Critic for Short Video Recommendation. CoRR abs/2302.01680 (2023) - [i59]Qingpeng Cai, Shuchang Liu, Xueliang Wang, Tianyou Zuo, Wentao Xie, Bin Yang, Dong Zheng, Peng Jiang, Kun Gai:
Reinforcing User Retention in a Billion Scale Short Video Recommender System. CoRR abs/2302.01724 (2023) - [i58]Jianxin Chang, Chenbin Zhang, Zhiyi Fu, Xiaoxue Zang, Lin Guan, Jing Lu, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai:
TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou. CoRR abs/2302.02352 (2023) - [i57]Yuan Zhang, Xue Dong, Weijie Ding, Biao Li, Peng Jiang, Kun Gai:
Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems From a Multi-task Perspective. CoRR abs/2302.02657 (2023) - [i56]Weiqi Zhao, Dian Tang, Xin Chen, Dawei Lv, Daoli Ou, Biao Li, Peng Jiang, Kun Gai:
Disentangled Causal Embedding With Contrastive Learning For Recommender System. CoRR abs/2302.03248 (2023) - [i55]Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang, Kun Gai:
Multi-Task Recommendations with Reinforcement Learning. CoRR abs/2302.03328 (2023) - [i54]Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Kun Gai, Peng Jiang, Xiangyu Zhao, Yongfeng Zhang:
Exploration and Regularization of the Latent Action Space in Recommendation. CoRR abs/2302.03431 (2023) - [i53]Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang Song, Kun Gai, Ji-Rong Wen:
When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation. CoRR abs/2305.10822 (2023) - [i52]Jingcao Xu, Chaokun Wang, Cheng Wu, Yang Song, Kai Zheng, Xiaowei Wang, Changping Wang, Guorui Zhou, Kun Gai:
Multi-behavior Self-supervised Learning for Recommendation. CoRR abs/2305.18238 (2023) - [i51]Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai:
Generative Flow Network for Listwise Recommendation. CoRR abs/2306.02239 (2023) - [i50]Zhenghai Xue, Qingpeng Cai, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An:
State Regularized Policy Optimization on Data with Dynamics Shift. CoRR abs/2306.03552 (2023) - [i49]Ziyang Liu, Chaokun Wang, Jingcao Xu, Cheng Wu, Kai Zheng, Yang Song, Na Mou, Kun Gai:
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation. CoRR abs/2306.04095 (2023) - [i48]Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai:
Graph Contrastive Learning with Generative Adversarial Network. CoRR abs/2308.00535 (2023) - [i47]Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Depeng Jin, Yong Li:
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation. CoRR abs/2308.04086 (2023) - [i46]Yue Feng, Shuchang Liu, Zhenghai Xue, Qingpeng Cai, Lantao Hu, Peng Jiang, Kun Gai, Fei Sun:
A Large Language Model Enhanced Conversational Recommender System. CoRR abs/2308.06212 (2023) - [i45]Yang Jin, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin Chen, Chenyi Lei, An Liu, Chengru Song, Xiaoqiang Lei, Di Zhang, Wenwu Ou, Kun Gai, Yadong Mu:
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization. CoRR abs/2309.04669 (2023) - [i44]Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai:
KuaiSim: A Comprehensive Simulator for Recommender Systems. CoRR abs/2309.12645 (2023) - [i43]Zhenghai Xue, Qingpeng Cai, Tianyou Zuo, Bin Yang, Lantao Hu, Peng Jiang, Kun Gai, Bo An:
AdaRec: Adaptive Sequential Recommendation for Reinforcing Long-term User Engagement. CoRR abs/2310.03984 (2023) - [i42]Yuchong Sun, Che Liu, Jinwen Huang, Ruihua Song, Fuzheng Zhang, Di Zhang, Zhongyuan Wang, Kun Gai:
Parrot: Enhancing Multi-Turn Chat Models by Learning to Ask Questions. CoRR abs/2310.07301 (2023) - [i41]Jia-Yi Fu, Lei Lin, Xiaoyang Gao, Pengli Liu, Zhengzong Chen, Zhirui Yang, Shengnan Zhang, Xue Zheng, Yan Li, Yuliang Liu, Xucheng Ye, Yiqiao Liao, Chao Liao, Bin Chen, Chengru Song, Junchen Wan, Zijia Lin, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai:
KwaiYiiMath: Technical Report. CoRR abs/2310.07488 (2023) - [i40]Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai:
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems. CoRR abs/2310.10462 (2023) - [i39]Jiao Ou, Junda Lu, Che Liu, Yihong Tang, Fuzheng Zhang, Di Zhang, Zhongyuan Wang, Kun Gai:
DialogBench: Evaluating LLMs as Human-like Dialogue Systems. CoRR abs/2311.01677 (2023) - [i38]Lei Lin, Jia-Yi Fu, Pengli Liu, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Di Zhang, Kun Gai:
Ask One More Time: Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios. CoRR abs/2311.08154 (2023) - [i37]Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang:
Mixed Attention Network for Cross-domain Sequential Recommendation. CoRR abs/2311.08272 (2023) - [i36]Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li:
Inverse Learning with Extremely Sparse Feedback for Recommendation. CoRR abs/2311.08302 (2023) - 2022
- [c37]Xudong Gong, Qinlin Feng, Yuan Zhang, Jiangling Qin, Weijie Ding, Biao Li, Peng Jiang, Kun Gai:
Real-time Short Video Recommendation on Mobile Devices. CIKM 2022: 3103-3112 - [c36]Ruohan Zhan, Changhua Pei, Qiang Su, Jianfeng Wen, Xueliang Wang, Guanyu Mu, Dong Zheng, Peng Jiang, Kun Gai:
Deconfounding Duration Bias in Watch-time Prediction for Video Recommendation. KDD 2022: 4472-4481 - 2021
- [c35]Chao Du, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Yifan Zeng, Xiaoqiang Zhu, Jian Xu, Kun Gai, Kuang-Chih Lee:
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning. KDD 2021: 2792-2801 - [c34]Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai:
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising. WSDM 2021: 993-1001 - [i35]Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai, Xiaoqiang Zhu:
Truncation-Free Matching System for Display Advertising at Alibaba. CoRR abs/2102.09283 (2021) - 2020
- [c33]Bo Wang, Quan Chen, Min Zhou, Zhiqiang Zhang, Xiaogang Jin, Kun Gai:
Progressive Feature Polishing Network for Salient Object Detection. AAAI 2020: 12128-12135 - [c32]Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai:
Sequential Advertising Agent with Interpretable User Hidden Intents. AAMAS 2020: 1966-1968 - [c31]Liyi Guo, Rui Lu, Haoqi Zhang, Junqi Jin, Zhenzhe Zheng, Fan Wu, Jin Li, Haiyang Xu, Han Li, Wenkai Lu, Jian Xu, Kun Gai:
A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction. CIKM 2020: 2501-2508 - [c30]Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai:
Learning to Infer User Hidden States for Online Sequential Advertising. CIKM 2020: 2677-2684 - [c29]Qi Pi, Guorui Zhou, Yujing Zhang, Zhe Wang, Lejian Ren, Ying Fan, Xiaoqiang Zhu, Kun Gai:
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction. CIKM 2020: 2685-2692 - [c28]Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai:
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising. ICML 2020: 4060-4070 - [c27]Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai:
Learning Optimal Tree Models under Beam Search. ICML 2020: 11650-11659 - [c26]Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai:
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. IJCAI 2020: 3437-3443 - [c25]Chao Deng, Hao Wang, Qing Tan, Jian Xu, Kun Gai:
Calibrating User Response Predictions in Online Advertising. ECML/PKDD (4) 2020: 208-223 - [c24]Jiarui Jin, Yuchen Fang, Weinan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai:
A Deep Recurrent Survival Model for Unbiased Ranking. SIGIR 2020: 29-38 - [i34]Jiarui Jin, Yuchen Fang, Weinan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai:
A Deep Recurrent Survival Model for Unbiased Ranking. CoRR abs/2004.14714 (2020) - [i33]Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai:
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. CoRR abs/2005.04355 (2020) - [i32]Qi Pi, Xiaoqiang Zhu, Guorui Zhou, Yujing Zhang, Zhe Wang, Lejian Ren, Ying Fan, Kun Gai:
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction. CoRR abs/2006.05639 (2020) - [i31]Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai:
DCAF: A Dynamic Computation Allocation Framework for Online Serving System. CoRR abs/2006.09684 (2020) - [i30]Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai:
Learning Optimal Tree Models Under Beam Search. CoRR abs/2006.15408 (2020) - [i29]Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai:
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising. CoRR abs/2006.16312 (2020) - [i28]Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai:
COLD: Towards the Next Generation of Pre-Ranking System. CoRR abs/2007.16122 (2020) - [i27]Liyi Guo, Rui Lu, Haoqi Zhang, Junqi Jin, Zhenzhe Zheng, Fan Wu, Jin Li, Haiyang Xu, Han Li, Wenkai Lu, Jian Xu, Kun Gai:
A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction. CoRR abs/2008.08931 (2020) - [i26]Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai:
Learning to Infer User Hidden States for Online Sequential Advertising. CoRR abs/2009.01453 (2020) - [i25]Guorui Zhou, Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Na Mou, Xinchen Luo, Chi Zhang, Xianjie Qiao, Shiming Xiang, Kun Gai, Xiaoqiang Zhu, Jian Xu:
CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction. CoRR abs/2011.05625 (2020) - [i24]Chao Du, Yifan Zeng, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Xiaoqiang Zhu, Jian Xu, Kun Gai:
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning. CoRR abs/2012.02298 (2020) - [i23]Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai:
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising. CoRR abs/2012.02930 (2020)
2010 – 2019
- 2019
- [c23]Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai:
Deep Interest Evolution Network for Click-Through Rate Prediction. AAAI 2019: 5941-5948 - [c22]Dagui Chen, Junqi Jin, Weinan Zhang, Fei Pan, Lvyin Niu, Chuan Yu, Jun Wang, Han Li, Jian Xu, Kun Gai:
Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds. CIKM 2019: 2527-2535 - [c21]Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Xiaotian Hao, Yixi Wang, Han Li, Jian Xu, Kun Gai:
Learning Adaptive Display Exposure for Real-Time Advertising. CIKM 2019: 2595-2603 - [c20]Zhangming Chan, Xiuying Chen, Yongliang Wang, Juntao Li, Zhiqiang Zhang, Kun Gai, Dongyan Zhao, Rui Yan:
Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation. EMNLP/IJCNLP (1) 2019: 4958-4967 - [c19]Yuchi Zhang, Yongliang Wang, Liping Zhang, Zhiqiang Zhang, Kun Gai:
Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder. ICASSP 2019: 2767-2771 - [c18]Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai:
Bid Optimization by Multivariable Control in Display Advertising. KDD 2019: 1966-1974 - [c17]Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai:
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction. KDD 2019: 2671-2679 - [c16]Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai:
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems. NeurIPS 2019: 3973-3982 - [c15]Kan Ren, Jiarui Qin, Yuchen Fang, Weinan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai:
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction. SIGIR 2019: 565-574 - [i22]Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai:
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems. CoRR abs/1902.07565 (2019) - [i21]Yuchi Zhang, Yongliang Wang, Liping Zhang, Zhiqiang Zhang, Kun Gai:
Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder. CoRR abs/1903.10842 (2019) - [i20]Kan Ren, Jiarui Qin, Yuchen Fang, Weinan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai:
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction. CoRR abs/1905.00758 (2019) - [i19]Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai:
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction. CoRR abs/1905.09248 (2019) - [i18]Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai:
Bid Optimization by Multivariable Control in Display Advertising. CoRR abs/1905.10928 (2019) - [i17]Guorui Zhou, Kailun Wu, Weijie Bian, Zhao Yang, Xiaoqiang Zhu, Kun Gai:
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling. CoRR abs/1906.10304 (2019) - [i16]Dagui Chen, Junqi Jin, Weinan Zhang, Fei Pan, Lvyin Niu, Chuan Yu, Jun Wang, Han Li, Jian Xu, Kun Gai:
Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds. CoRR abs/1908.06698 (2019) - [i15]Bo Wang, Quan Chen, Min Zhou, Zhiqiang Zhang, Xiaogang Jin, Kun Gai:
Progressive Feature Polishing Network for Salient Object Detection. CoRR abs/1911.05942 (2019) - 2018
- [c14]Guorui Zhou, Ying Fan, Runpeng Cui, Weijie Bian, Xiaoqiang Zhu, Kun Gai:
Rocket Launching: A Universal and Efficient Framework for Training Well-Performing Light Net. AAAI 2018: 4580-4587 - [c13]Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Jian Xu, Kun Gai:
Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising. CIKM 2018: 1443-1451 - [c12]Tiezheng Ge, Liqin Zhao, Guorui Zhou, Keyu Chen, Shuying Liu, Huiming Yi, Zelin Hu, Bochao Liu, Peng Sun, Haoyu Liu, Pengtao Yi, Sui Huang, Zhiqiang Zhang, Xiaoqiang Zhu, Yu Zhang, Kun Gai:
Image Matters: Visually Modeling User Behaviors Using Advanced Model Server. CIKM 2018: 2087-2095 - [c11]Junqi Jin, Chengru Song, Han Li, Kun Gai, Jun Wang, Weinan Zhang:
Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising. CIKM 2018: 2193-2201 - [c10]Guorui Zhou, Xiaoqiang Zhu, Chengru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai:
Deep Interest Network for Click-Through Rate Prediction. KDD 2018: 1059-1068 - [c9]Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai:
Learning Tree-based Deep Model for Recommender Systems. KDD 2018: 1079-1088 - [c8]Quan Chen, Tiezheng Ge, Yanyu Xu, Zhiqiang Zhang, Xinxin Yang, Kun Gai:
Semantic Human Matting. ACM Multimedia 2018: 618-626 - [c7]Xiao Ma, Liqin Zhao, Guan Huang, Zhi Wang, Zelin Hu, Xiaoqiang Zhu, Kun Gai:
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate. SIGIR 2018: 1137-1140 - [i14]Han Zhu, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai:
Learning Tree-based Deep Model for Recommender Systems. CoRR abs/1801.02294 (2018) - [i13]Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Kun Gai:
Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising. CoRR abs/1802.08365 (2018) - [i12]Junqi Jin, Chengru Song, Han Li, Kun Gai, Jun Wang, Weinan Zhang:
Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising. CoRR abs/1802.09756 (2018) - [i11]Xiao Ma, Liqin Zhao, Guan Huang, Zhi Wang, Zelin Hu, Xiaoqiang Zhu, Kun Gai:
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate. CoRR abs/1804.07931 (2018) - [i10]Quan Chen, Tiezheng Ge, Yanyu Xu, Zhiqiang Zhang, Xinxin Yang, Kun Gai:
Semantic Human Matting. CoRR abs/1809.01354 (2018) - [i9]Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Weinan Zhang, Jun Wang, Yixi Wang, Han Li, Jian Xu, Kun Gai:
Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning. CoRR abs/1809.03149 (2018) - [i8]Di Wu, Cheng Chen, Xun Yang, Xiujun Chen, Qing Tan, Jian Xu, Kun Gai:
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising. CoRR abs/1809.03152 (2018) - [i7]Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai:
Deep Interest Evolution Network for Click-Through Rate Prediction. CoRR abs/1809.03672 (2018) - 2017
- [c6]Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai:
Optimized Cost per Click in Taobao Display Advertising. KDD 2017: 2191-2200 - [i6]Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai:
Optimized Cost per Click in Taobao Display Advertising. CoRR abs/1703.02091 (2017) - [i5]Kun Gai, Xiaoqiang Zhu, Han Li, Kai Liu, Zhe Wang:
Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction. CoRR abs/1704.05194 (2017) - [i4]Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Xiao Ma, Yanghui Yan, Xingya Dai, Han Zhu, Junqi Jin, Han Li, Kun Gai:
Deep Interest Network for Click-Through Rate Prediction. CoRR abs/1706.06978 (2017) - [i3]Guorui Zhou, Ying Fan, Runpeng Cui, Weijie Bian, Xiaoqiang Zhu, Kun Gai:
Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net. CoRR abs/1708.04106 (2017) - [i2]Tiezheng Ge, Liqin Zhao, Guorui Zhou, Keyu Chen, Shuying Liu, Huiming Yi, Zelin Hu, Bochao Liu, Peng Sun, Haoyu Liu, Pengtao Yi, Sui Huang, Zhiqiang Zhang, Xiaoqiang Zhu, Yu Zhang, Kun Gai:
Image Matters: Jointly Train Advertising CTR Model with Image Representation of Ad and User Behavior. CoRR abs/1711.06505 (2017) - 2013
- [c5]Han Li, Kun Gai, Pinghua Gong, Changshui Zhang:
Efficient blind separation of reflection layers with nonparametric transformations. ICASSP 2013: 1641-1645 - 2012
- [j2]Kun Gai, Zhenwei Shi, Changshui Zhang:
Blind Separation of Superimposed Moving Images Using Image Statistics. IEEE Trans. Pattern Anal. Mach. Intell. 34(1): 19-32 (2012) - [i1]Han Li, Kun Gai, Pinghua Gong, Changshui Zhang:
Efficient Superimposition Recovering Algorithm. CoRR abs/1211.4307 (2012) - 2011
- [j1]Pinghua Gong, Kun Gai, Changshui Zhang:
Efficient Euclidean projections via Piecewise Root Finding and its application in gradient projection. Neurocomputing 74(17): 2754-2766 (2011) - 2010
- [c4]Kun Gai, Changshui Zhang:
Learning Discriminative Piecewise Linear Models with Boundary Points. AAAI 2010: 444-450 - [c3]Kun Gai, Guangyun Chen, Changshui Zhang:
Learning Kernels with Radiuses of Minimum Enclosing Balls. NIPS 2010: 649-657
2000 – 2009
- 2009
- [c2]Kun Gai, Zhenwei Shi, Changshui Zhang:
Blind separation of superimposed images with unknown motions. CVPR 2009: 1881-1888 - 2008
- [c1]Kun Gai, Zhenwei Shi, Changshui Zhang:
Blindly separating mixtures of multiple layers with spatial shifts. CVPR 2008
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-18 21:46 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
