dblp: Lingkai Kong (original) (raw)

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2020 – today

• 2026
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  [j13]
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    Zhuhua Hu, Yifeng Sun, Yaochi Zhao, Wei Wu, Lingkai Kong, Keli Chen:
    MSIF-SSTR: A "Quick smuggler" smuggling speedboat trajectory recognition method based on multi-source information fusion. Expert Syst. Appl. 312: 131525 (2026)
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  [c41]
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    Lingkai Kong, Haichuan Wang, Charles A. Emogor, Vincent Börsch-Supan, Lily Xu, Milind Tambe:
    Generative AI Against Poaching: Latent Composite Flow Matching for Poaching Prediction. AAAI 2026: 40279-40286
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  [i45]
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    Lingkai Kong, Cheol Woo Kim, Davin Choo, Milind Tambe:
    Generative AI for Social Impact. CoRR abs/2601.04238 (2026)
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  [i44]
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    Akseli Kangaslahti, Davin Choo, Lingkai Kong, Milind Tambe, Alastair van Heerden, Cheryl Johnson:
    Policy-Embedded Graph Expansion: Networked HIV Testing with Diffusion-Driven Network Samples. CoRR abs/2601.16233 (2026)
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  [i43]
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    Lingkai Kong, Anagha Satish, Hezi Jiang, Akseli Kangaslahti, Andrew Ma, Wenbo Chen, Mingxiao Song, Lily Xu, Milind Tambe:
    Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions. CoRR abs/2601.22211 (2026)
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  [i42]
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    Haichuan Wang, Tao Lin, Lingkai Kong, Ce Li, Hezi Jiang, Milind Tambe:
    Reward Shaping for Inference-Time Alignment: A Stackelberg Game Perspective. CoRR abs/2602.02572 (2026)
• 2025
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  [j12]
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    Lingkai Kong, Boying Zhao, Hongyu Li, Wei He, You Cao, Guohui Zhou:
    A medical assistant decision-making method based on interval belief rule base with explainability. Intell. Data Anal. 29(2): 490-512 (2025)
• 
  [j11]
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    Boying Zhao, Lingkai Kong, Wei He, Guohui Zhou, Hailong Zhu:
    A Fault Diagnosis Method for Manufacturing System Based on Adaptive BRB Considering Environmental Disturbance. Int. J. Fuzzy Syst. 27(4): 1038-1051 (2025)
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  [j10]
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    Xiaomeng Yang, Sen Qu, Lingkai Kong:
    The Impact of Cooperation Network Evolution on Communication Technology Innovation: A Network Interaction Perspective. Syst. 13(2): 126 (2025)
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  [c40]
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    Shresth Verma, Alayna Nguyen, Niclas Boehmer, Lingkai Kong, Milind Tambe:
    PRIORITY2REWARD: Incorporating Healthworker Preferences for Resource Allocation Planning. AAAI 2025: 29709-29711
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  [c39]
  Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M. Ferber, Yian Ma, Carla P. Gomes, Chao Zhang:
  Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. AISTATS 2025: 4582-4590
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  [c38]
  Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang:
  Efficient Evolutionary Search Over Chemical Space with Large Language Models. ICLR 2025
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  [c37]
  Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao:
  Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. ICLR 2025
• 
  [c36]
  Cheol Woo Kim, Jai Moondra, Shresth Verma, Madeleine Pollack, Lingkai Kong, Milind Tambe, Swati Gupta:
  Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning. ICML 2025
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  [c35]
  Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang:
  LLM-Augmented Chemical Synthesis and Design Decision Programs. ICML 2025
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  [c34]
  Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang:
  DF2: Distribution-Free Decision-Focused Learning. UAI 2025: 2269-2290
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  [c33]
  Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe:
  Robust Optimization with Diffusion Models for Green Security. UAI 2025: 2325-2344
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  [c32]
  Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe:
  What is the Right Notion of Distance between Predict-then-Optimize Tasks? UAI 2025: 3570-3586
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  [i41]
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    Cheol Woo Kim, Jai Moondra, Shresth Verma, Madeleine Pollack, Lingkai Kong, Milind Tambe, Swati Gupta:
    Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning. CoRR abs/2502.09724 (2025)
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  [i40]
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    Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe:
    Robust Optimization with Diffusion Models for Green Security. CoRR abs/2503.05730 (2025)
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  [i39]
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    Sarah Martinson, Lingkai Kong, Cheol Woo Kim, Aparna Taneja, Milind Tambe:
    LLM-based Agent Simulation for Maternal Health Interventions: Uncertainty Estimation and Decision-focused Evaluation. CoRR abs/2503.22719 (2025)
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  [i38]
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    Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang:
    LLM-Augmented Chemical Synthesis and Design Decision Programs. CoRR abs/2505.07027 (2025)
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  [i37]
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    Lingkai Kong, Haichuan Wang, Tonghan Wang, Guojun Xiong, Milind Tambe:
    Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data. CoRR abs/2505.23062 (2025)
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  [i36]
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    Lingkai Kong, Haichuan Wang, Charles A. Emogor, Vincent Börsch-Supan, Lily Xu, Milind Tambe:
    Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation. CoRR abs/2508.14342 (2025)
• 
  [i35]
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    Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang:
    Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process. CoRR abs/2508.17097 (2025)
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  [i34]
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    Zihao Zhao, Christopher Yeh, Lingkai Kong, Kai Wang:
    Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization. CoRR abs/2510.11590 (2025)
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  [i33]
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    Rongzhi Zhang, Liqin Ye, Yuzhao Heng, Xiang Chen, Tong Yu, Lingkai Kong, Sudheer Chava, Chao Zhang:
    Precise Attribute Intensity Control in Large Language Models via Targeted Representation Editing. CoRR abs/2510.12121 (2025)
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  [i32]
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    Lingkai Kong, Molei Tao, Yang Liu, Bryan Wang, Jinmiao Fu, Chien-Chih Wang, Huidong Liu:
    AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport. CoRR abs/2510.15038 (2025)
• 
  [i31]
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    Songyang Gao, Yuzhe Gu, Zijian Wu, Lingkai Kong, Wenwei Zhang, Zhongrui Cai, Fan Zheng, Tianyou Ma, Junhao Shen, Haiteng Zhao, Duanyang Zhang, Huilun Zhang, Kuikun Liu, Chengqi Lyu, Yanhui Duan, Chiyu Chen, Ningsheng Ma, Jianfei Gao, Han Lyu, Dahua Lin, Kai Chen:
    Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving. CoRR abs/2512.10739 (2025)
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  [i30]
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    Zijian Wu, Lingkai Kong, Wenwei Zhang, Songyang Gao, Yuzhe Gu, Zhongrui Cai, Tianyou Ma, Yuhong Liu, Zhi Wang, Runyuan Ma, Guangyu Wang, Wei Li, Conghui He, Dahua Lin, Kai Chen:
    OPV: Outcome-based Process Verifier for Efficient Long Chain-of-Thought Verification. CoRR abs/2512.10756 (2025)
• 
  [i29]
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    Julian Kleutgens, Claudio Battiloro, Lingkai Kong, Benjamin Grewe, Francesca Dominici, Mauricio Tec:
    Guided Transfer Learning for Discrete Diffusion Models. CoRR abs/2512.10877 (2025)
• 2024
• 
  [j9]
  Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang:
  MUBen: Benchmarking the Uncertainty of Molecular Representation Models. Trans. Mach. Learn. Res. 2024 (2024)
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  [c31]
  Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang:
  Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process. AISTATS 2024: 4582-4590
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  [c30]
  Lingkai Kong, Molei Tao:
  Convergence of Kinetic Langevin Monte Carlo on Lie groups. COLT 2024: 3011-3063
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  [c29]
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    Shresth Verma, Niclas Boehmer, Lingkai Kong, Milind Tambe:
    Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards. GameSec (1) 2024: 376-394
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  [c28]
  Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash:
  Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. ICML 2024: 31312-31325
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  [c27]
  Lingkai Kong, Molei Tao:
  Quantitative Convergences of Lie Group Momentum Optimizers. NeurIPS 2024
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  [c26]
  Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, Yuchen Zhuang, Yifei Zhou, Yue Song, Rongzhi Zhang, Kai Wang, Chao Zhang:
  Aligning Large Language Models with Representation Editing: A Control Perspective. NeurIPS 2024
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  [c25]
  Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash:
  Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis. NeurIPS 2024
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  [i28]
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    Haorui Wang, Rongzhi Zhang, Yinghao Li, Lingkai Kong, Yuchen Zhuang, Xiusi Chen, Chao Zhang:
    TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidance. CoRR abs/2401.13849 (2024)
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  [i27]
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    Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Haorui Wang, Dongxia Wu, Aaron M. Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang:
    Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. CoRR abs/2402.18012 (2024)
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  [i26]
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    Lingkai Kong, Molei Tao:
    Convergence of Kinetic Langevin Monte Carlo on Lie groups. CoRR abs/2403.12012 (2024)
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  [i25]
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    Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao:
    Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. CoRR abs/2405.16381 (2024)
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  [i24]
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    Lingkai Kong, Molei Tao:
    Quantitative Convergences of Lie Group Momentum Optimizers. CoRR abs/2405.20390 (2024)
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  [i23]
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    Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, Yuchen Zhuang, Yifei Zhou, Yue Song, Rongzhi Zhang, Kai Wang, Chao Zhang:
    Aligning Large Language Models with Representation Editing: A Control Perspective. CoRR abs/2406.05954 (2024)
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  [i22]
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    Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash:
    Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis. CoRR abs/2406.08627 (2024)
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  [i21]
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    Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash:
    Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. CoRR abs/2406.09130 (2024)
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  [i20]
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    Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Streith-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang:
    Efficient Evolutionary Search Over Chemical Space with Large Language Models. CoRR abs/2406.16976 (2024)
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  [i19]
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    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
    Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. CoRR abs/2407.02641 (2024)
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  [i18]
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    Shresth Verma, Niclas Boehmer, Lingkai Kong, Milind Tambe:
    Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards. CoRR abs/2408.12112 (2024)
• 
  [i17]
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    Chen Chen, Lingkai Kong, Gongjie Li, Molei Tao:
    DeepTTV: Deep Learning Prediction of Hidden Exoplanet From Transit Timing Variations. CoRR abs/2409.04557 (2024)
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  [i16]
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    Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe:
    What is the Right Notion of Distance between Predict-then-Optimize Tasks? CoRR abs/2409.06997 (2024)
• 2023
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  [j8]
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    Yonghong Ma, Xiaomeng Yang, Sen Qu, Lingkai Kong:
    Characteristics and driving factors of the technology cooperation network evolution: a case study of solid waste treatment field in China. Technol. Anal. Strateg. Manag. 35(5): 508-522 (2023)
• 
  [c24]
  Lingkai Kong, Yuqing Wang, Molei Tao:
  Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. ICLR 2023
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  [c23]
  Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang:
  Autoregressive Diffusion Model for Graph Generation. ICML 2023: 17391-17408
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  [c22]
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    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
    When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. KDD 2023: 1057-1072
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  [c21]
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    Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang:
    DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling. KDD 2023: 3674-3686
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  [c20]
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    Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang:
    Uncertainty Quantification in Deep Learning. KDD 2023: 5809-5810
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  [c19]
  Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang:
  AdaPlanner: Adaptive Planning from Feedback with Language Models. NeurIPS 2023
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  [i15]
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    Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang:
    AdaPlanner: Adaptive Planning from Feedback with Language Models. CoRR abs/2305.16653 (2023)
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  [i14]
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    Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang:
    DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling. CoRR abs/2305.19395 (2023)
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  [i13]
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    Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang:
    MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction. CoRR abs/2306.10060 (2023)
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  [i12]
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    Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang:
    Autoregressive Diffusion Model for Graph Generation. CoRR abs/2307.08849 (2023)
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  [i11]
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    Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang:
    DF2: Distribution-Free Decision-Focused Learning. CoRR abs/2308.05889 (2023)
• 2022
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  [j7]
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    Yonghong Ma, Xiaomeng Yang, Sen Qu, Lingkai Kong:
    Research on the formation mechanism of big data technology cooperation networks: empirical evidence from China. Scientometrics 127(3): 1273-1294 (2022)
• 
  [j6]
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    Wei Chen, Chaoran Lin, Chuanyun Li, Lingkai Kong, Zaoli Yang:
    Tracing the Evolution of 3-D Printing Technology in China Using LDA-Based Patent Abstract Mining. IEEE Trans. Engineering Management 69(4): 1135-1145 (2022)
• 
  [c18]
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    Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, Chao Zhang:
    AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models. NAACL-HLT 2022: 1422-1436
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  [c17]
  Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang:
  End-to-end Stochastic Optimization with Energy-based Model. NeurIPS 2022
• 
  [c16]
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    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
    CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. WWW 2022: 3174-3185
• 
  [i10]
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    Lingkai Kong, Yuqing Wang, Molei Tao:
    Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. CoRR abs/2205.14173 (2022)
• 
  [i9]
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    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
    PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. CoRR abs/2206.07940 (2022)
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  [i8]
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    Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang:
    End-to-End Stochastic Optimization with Energy-Based Model. CoRR abs/2211.13837 (2022)
• 2021
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  [j5]
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    Yonghong Ma, Lingkai Kong, Xiaomeng Yang, Chaoran Lin:
    Innovation Cooperation Network Evolution About Green Building Technology With Government Intervention: Based on Evolutionary Game Theory. IEEE Access 9: 142289-142301 (2021)
• 
  [c15]
  Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
  When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. NeurIPS 2021: 19796-19807
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  [i7]
  Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
  When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. CoRR abs/2106.03904 (2021)
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  [i6]
  Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
  CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. CoRR abs/2109.07438 (2021)
• 
  [i5]
  Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, Chao Zhang:
  ATM: An Uncertainty-aware Active Self-training Framework for Label-efficient Text Classification. CoRR abs/2112.08787 (2021)
• 2020
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  [c14]
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    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
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  [c13]
  Lingkai Kong, Jimeng Sun, Chao Zhang:
  SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates. ICML 2020: 5405-5415
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  [c12]
  Lingkai Kong, Molei Tao:
  Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function. NeurIPS 2020
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  [i4]
  Lingkai Kong, Molei Tao:
  Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function. CoRR abs/2002.06189 (2020)
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  [i3]
  Lingkai Kong, Jimeng Sun, Chao Zhang:
  SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates. CoRR abs/2008.10546 (2020)
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  [i2]
  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

• 2018
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  [c11]
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    Liang Wu, Lingkai Kong, Zaichen Zhang, Jian Dang, Huaping Liu:
    Wide-range Dimmable Clipped Flip-OFDM For Indoor Visible Light Communications. ICCC 2018: 121-125
• 
  [c10]
  Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha:
  Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. UAI 2018: 83-92
• 
  [i1]
  Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha:
  Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. CoRR abs/1807.08237 (2018)
• 2016
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  [c9]
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    Lingkai Kong, Congcong Cao, Siyuan Zhang, Mengchao Li, Liang Wu, Zaichen Zhang, Jian Dang:
    A Novel OFDM Scheme for VLC Systems Under LED Nonlinear Constraints. ChinaCom (1) 2016: 393-402
• 2014
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  [c8]
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    Nai-Chung Kuo, Bonjern Yang, Chaoying Wu, Lingkai Kong, Angie Wang, Michael Reiha, Elad Alon, Ali M. Niknejad, Borivoje Nikolic:
    A frequency-reconfigurable multi-standard 65nm CMOS digital transmitter with LTCC interposers. A-SSCC 2014: 345-348
• 2013
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  [j4]
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    Lu Ye, Jiashu Chen, Lingkai Kong, Elad Alon, Ali M. Niknejad:
    Design Considerations for a Direct Digitally Modulated WLAN Transmitter With Integrated Phase Path and Dynamic Impedance Modulation. IEEE J. Solid State Circuits 48(12): 3160-3177 (2013)
• 
  [c7]
  John Crossley, Alberto Puggelli, Hanh-Phuc Le, B. Yang, R. Nancollas, Kwangmo Jung, Lingkai Kong, Nathan Narevsky, Yue Lu, Nicholas Sutardja, E. J. An, Alberto L. Sangiovanni-Vincentelli, Elad Alon:
  BAG: a designer-oriented integrated framework for the development of AMS circuit generators. ICCAD 2013: 74-81
• 
  [c6]
  • 
  • 
  • 
  • 
    Lingkai Kong, Dongjin Seo, Elad Alon:
    A 50mW-TX 65mW-RX 60GHz 4-element phased-array transceiver with integrated antennas in 65nm CMOS. ISSCC 2013: 234-235
• 
  [c5]
  • 
  • 
  • 
  • 
    Lu Ye, Jiashu Chen, Lingkai Kong, Philippe Cathelin, Elad Alon, Ali Niknejad:
    A digitally modulated 2.4GHz WLAN transmitter with integrated phase path and dynamic load modulation in 65nm CMOS. ISSCC 2013: 330-331
• 2012
• 
  [j3]
  • 
  • 
  • 
  • 
    Chintan Thakkar, Lingkai Kong, Kwangmo Jung, Antoine Frappé, Elad Alon:
    A 10 Gb/s 45 mW Adaptive 60 GHz Baseband in 65 nm CMOS. IEEE J. Solid State Circuits 47(4): 952-968 (2012)
• 
  [c4]
  • 
  • 
  • 
  • 
    Lingkai Kong, Elad Alon:
    A 21.5mW 10+Gb/s mm-Wave phased-array transmitter in 65nm CMOS. VLSIC 2012: 52-53
• 2011
• 
  [j2]
  • 
  • 
  • 
  • 
    Maryam Tabesh, Jiashu Chen, Cristian Marcu, Lingkai Kong, Shinwon Kang, Ali M. Niknejad, Elad Alon:
    A 65 nm CMOS 4-Element Sub-34 mW/Element 60 GHz Phased-Array Transceiver. IEEE J. Solid State Circuits 46(12): 3018-3032 (2011)
• 
  [c3]
  • 
  • 
  • 
  • 
    Lingkai Kong, Yue Lu, Elad Alon:
    A multi-GHz area-efficient comparator with dynamic offset cancellation. CICC 2011: 1-4
• 
  [c2]
  • 
  • 
  • 
  • 
    Maryam Tabesh, Jiashu Chen, Cristian Marcu, Lingkai Kong, Shinwon Kang, Elad Alon, Ali Niknejad:
    A 65nm CMOS 4-element Sub-34mW/element 60GHz phased-array transceiver. ISSCC 2011: 166-168

2000 – 2009

• 2009
• 
  [j1]
  • 
  • 
  • 
  • 
    Cristian Marcu, Debopriyo Chowdhury, Chintan Thakkar, Jung-Dong Park, Lingkai Kong, Maryam Tabesh, Yanjie Wang, Bagher Afshar, Abhinav Gupta, Amin Arbabian, Simone Gambini, Reza Zamani, Elad Alon, Ali M. Niknejad:
    A 90 nm CMOS Low-Power 60 GHz Transceiver With Integrated Baseband Circuitry. IEEE J. Solid State Circuits 44(12): 3434-3447 (2009)
• 
  [c1]
  • 
  • 
  • 
  • 
    Cristian Marcu, Debopriyo Chowdhury, Chintan Thakkar, Lingkai Kong, Maryam Tabesh, Jung-Dong Park, Yanjie Wang, Bagher Afshar, Abhinav Gupta, Amin Arbabian, Simone Gambini, Reza Zamani, Ali M. Niknejad, Elad Alon:
    A 90nm CMOS low-power 60GHz transceiver with integrated baseband circuitry. ISSCC 2009: 314-315

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