Lingkai Kong
25 papers · 2020–2026 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (63) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Triple Crown
π
Grand Slam
π€
Dynamic Duo
(15)
β‘
Prolific Year Β· Productive
π
Renaissance Researcher
(6)
π
Century Club Β· Bronze
β
The Questioner
ποΈ
Keyword Collector
(127)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(22)
Optimization & Theory
(14)
Artificial Intelligence
(13)
Deep Learning
(11)
Core AI
(10)
Learning Types
(8)
Application Areas
(6)
Models
(6)
Mathematics & Optimization
(5)
Optimization
(5)
Bayesian & Probabilistic Β· Machine Learning
(4)
Natural Language Processing
(3)
Architectures
(3)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Core Methods
(3)
Keywords
diffusion model
(4)
large language model
(4)
uncertainty quantification
(3)
lie group
(3)
optimal transport
(2)
generative model
(2)
decision-focused learning
(2)
black-box optimization
(2)
neural process
(2)
vision transformer
(1)
game theory
(1)
domain adaptation
(1)
text classification
(1)
graph classification
(1)
stochastic gradient descent
(1)
stochastic optimization
(1)
transfer learning
(1)
attention mechanism
(1)
variational inference
(1)
langevin dynamics
(1)
Papers
Generative AI Against Poaching: Latent Composite Flow Matching for Poaching Prediction
AAAI 2026
DF$^2$: Distribution-Free Decision-Focused Learning
UAI 2025
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
AISTATS 2025
Efficient Evolutionary Search Over Chemical Space with Large Language Models
ICLR 2025
LLM-Augmented Chemical Synthesis and Design Decision Programs
ICML 2025
Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning
ICML 2025
PRIORITY2REWARD: Incorporating Healthworker Preferences for Resource Allocation Planning
AAAI 2025
Robust Optimization with Diffusion Models for Green Security
UAI 2025
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
ICLR 2025
What is the Right Notion of Distance between Predict-then-Optimize Tasks?
UAI 2025
Aligning Large Language Models with Representation Editing: A Control Perspective
NeurIPS 2024
Convergence of Kinetic Langevin Monte Carlo on Lie groups
COLT 2024
Quantitative Convergences of Lie Group Momentum Optimizers
NeurIPS 2024
Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis
NeurIPS 2024
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
ICML 2024
Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process
AISTATS 2024
AdaPlanner: Adaptive Planning from Feedback with Language Models
NeurIPS 2023
Autoregressive Diffusion Model for Graph Generation
ICML 2023
Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport
ICLR 2023
AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models
NAACL 2022
End-to-end Stochastic Optimization with Energy-based Model
NeurIPS 2022
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
NeurIPS 2021
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
EMNLP 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
ICML 2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function
NeurIPS 2020