Jie Lu

Autonomous Concept Drift Threshold Determination AAAI 2026 Discovering Mixture Skills for Unsupervised Reinforcement Learning AAAI 2026 Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning AAAI 2026 PARS: Partial-Label-Learning-inspired Recommender Systems AAAI 2026 TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG ACL 2026 Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards ICLR 2025 Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space ICLR 2025 Early Concept Drift Detection via Prediction Uncertainty AAAI 2025 Functional Stochastic Gradient MCMC for Bayesian Neural Networks AISTATS 2025 HetGCoT: Heterogeneous Graph-Enhanced Chain-of-Thought LLM Reasoning for Academic Question Answering EMNLP 2025 On the Provable Importance of Gradients for Autonomous Language-Assisted Image Clustering ICCV 2025 Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer ICLR 2025 A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points IJCAI 2024 Functional Wasserstein Bridge Inference for Bayesian Deep Learning UAI 2024 Functional Wasserstein Variational Policy Optimization UAI 2024 GMM-CoRegNet: A Multimodal Groupwise Registration Framework Based on Gaussian Mixture Model MICCAI 2024 Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning IJCAI 2024 Knowledge Distillation with Auxiliary Variable ICML 2024 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection NeurIPS 2024 LuoShen: A Hyper-Converged Programmable Gateway for Multi-Tenant Multi-Service Edge Clouds NSDI 2024 Online Boosting Adaptive Learning under Concept Drift for Multistream Classification AAAI 2024 On the Learnability of Out-of-distribution Detection JMLR 2024 Meta OOD Learning For Continuously Adaptive OOD Detection ICCV 2023 Is Out-of-Distribution Detection Learnable? NeurIPS 2022 Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples AAAI 2022 How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? AAAI 2021 Learning Bounds for Open-Set Learning ICML 2021 Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data NeurIPS 2021 Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation IJCAI 2020 Learning Deep Kernels for Non-Parametric Two-Sample Tests ICML 2020 Regional Concept Drift Detection and Density Synchronized Drift Adaptation IJCAI 2017 Improving Topic Model Stability for Effective Document Exploration IJCAI 2016 Summarizing Definition from Wikipedia ACL 2009