Lingkai Kong
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
24
Venues
11
Active years
2013–2026
Best venue rank
A*
Where they publish
Papers
24 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Generative AI Against Poaching: Latent Composite Flow Matching for Poaching Prediction. | Lingkai Kong, Haichuan Wang, Charles A. Emogor, Vincent Brsch-Supan, Lily Xu, Milind Tambe |
| 2025 | AAAI | PRIORITY2REWARD: Incorporating Healthworker Preferences for Resource Allocation Planning. | Shresth Verma, Alayna Nguyen, Niclas Boehmer, Lingkai Kong, Milind Tambe |
| 2025 | AISTATS | Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. | 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 |
| 2025 | ICLR | Efficient Evolutionary Search Over Chemical Space with Large Language Models. | Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Aln Aspuru-Guzik, Kirill Neklyudov, Chao Zhang |
| 2025 | ICLR | Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. | Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao |
| 2025 | ICML | Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning. | Cheol Woo Kim, Jai Moondra, Shresth Verma, Madeleine Pollack, Lingkai Kong, Milind Tambe, Swati Gupta |
| 2025 | ICML | LLM-Augmented Chemical Synthesis and Design Decision Programs. | Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang |
| 2025 | UAI | What is the Right Notion of Distance between Predict-then-Optimize Tasks? | Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe |
| 2025 | UAI | DF | Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang |
| 2025 | UAI | Robust Optimization with Diffusion Models for Green Security. | Lingkai Kong, Haichuan Wang, Yuqi Pan, Cheol Woo Kim, Mingxiao Song, Alayna Nguyen, Tonghan Wang, Haifeng Xu, Milind Tambe |
| 2024 | AISTATS | Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process. | Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang |
| 2024 | COLT | Convergence of Kinetic Langevin Monte Carlo on Lie groups. | Lingkai Kong, Molei Tao |
| 2024 | ICML | Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. | Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash |
| 2023 | ICLR | Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. | Lingkai Kong, Yuqing Wang, Molei Tao |
| 2023 | ICML | Autoregressive Diffusion Model for Graph Generation. | Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang |
| 2023 | KDD | When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. | Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodrguez, Chao Zhang, B. Aditya Prakash |
| 2023 | KDD | Uncertainty Quantification in Deep Learning. | Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang |
| 2023 | KDD | DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling. | Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang |
| 2022 | NAACL | AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models. | Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, Chao Zhang |
| 2022 | WWW | CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. | Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodrguez, Chao Zhang, B. Aditya Prakash |
| 2020 | EMNLP | Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. | Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang |
| 2020 | ICML | SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates. | Lingkai Kong, Jimeng Sun, Chao Zhang |
| 2018 | UAI | Learning Deep Hidden Nonlinear Dynamics from Aggregate Data. | Yisen Wang, Bo Dai, Lingkai Kong, Sarah Monazam Erfani, James Bailey, Hongyuan Zha |
| 2013 | ICCAD | BAG: a designer-oriented integrated framework for the development of AMS circuit generators. | 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 |