Peilin Zhao

CrystalDiT: Simple Diffusion Transformers for Crystal Generation AAAI 2026 PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction CVPR 2026 The Stackelberg Speaker: Optimizing Persuasive Communication in Social Deduction Games ACL 2026 COME: Test-time Adaption by Conservatively Minimizing Entropy ICLR 2025 Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity ICML 2025 HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting AAAI 2025 IgGM: A Generative Model for Functional Antibody and Nanobody Design ICLR 2025 Injecting Imbalance Sensitivity for Multi-Task Learning IJCAI 2025 Measuring Diversity in Synthetic Datasets ICML 2025 NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction ICML 2025 Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples ICML 2025 Scaling Diffusion Language Models via Adaptation from Autoregressive Models ICLR 2025 Self-Bootstrapping for Versatile Test-Time Adaptation ICML 2025 Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models ICLR 2025 Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025 Test-time Adapted Reinforcement Learning with Action Entropy Regularization ICML 2025 TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting ICLR 2025 Enhancing Neural Subset Selection: Integrating Background Information into Set Representations ICLR 2024 Latent Diffusion Transformer for Probabilistic Time Series Forecasting AAAI 2024 LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay EMNLP 2024 Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization ICML 2024 Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution ICLR 2024 SDformer: Similarity-driven Discrete Transformer For Time Series Generation NeurIPS 2024 SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases ICLR 2024 Test-Time Model Adaptation with Only Forward Passes ICML 2024 Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations IJCAI 2024 WatME: Towards Lossless Watermarking Through Lexical Redundancy ACL 2024 A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges IJCAI 2023 BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion ICLR 2023 Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition CVPR 2023 Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction IJCAI 2023 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023 Fairness-guided Few-shot Prompting for Large Language Models NeurIPS 2023 FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning ICML 2023 GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection NeurIPS 2023 Handling Missing Data via Max-Entropy Regularized Graph Autoencoder AAAI 2023 ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification AAAI 2023 On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023 Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023 Retaining Beneficial Information from Detrimental Data for Neural Network Repair NeurIPS 2023 Towards Stable Test-time Adaptation in Dynamic Wild World ICLR 2023 p-Laplacian Based Graph Neural Networks ICML 2022 Efficient Test-Time Model Adaptation without Forgetting ICML 2022 GNN-Retro: Retrosynthetic Planning with Graph Neural Networks AAAI 2022 Learning Neural Set Functions Under the Optimal Subset Oracle NeurIPS 2022 Local Augmentation for Graph Neural Networks ICML 2022 SVIP: Sequence VerIfication for Procedures in Videos CVPR 2022 UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup NeurIPS 2022 AdaXpert: Adapting Neural Architecture for Growing Data ICML 2021 Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization AISTATS 2021 Context-Aware Domain Adaptation in Semantic Segmentation WACV 2021 Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation ICCV 2021 Hierarchical Graph Capsule Network AAAI 2021 Meta-learning Hyperparameter Performance Prediction with Neural Processes ICML 2021 Meta-learning with an Adaptive Task Scheduler NeurIPS 2021 PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning AAAI 2021 Adversarial Sparse Transformer for Time Series Forecasting NeurIPS 2020 Aggregated Gradient Langevin Dynamics AAAI 2020 Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search ICML 2020 Contextualized Point-of-Interest Recommendation IJCAI 2020 Mastering Complex Control in MOBA Games with Deep Reinforcement Learning AAAI 2020 Relation-Aware Transformer for Portfolio Policy Learning IJCAI 2020 RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist NeurIPS 2020 Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks AAAI 2020 Towards Fast Adaptation of Neural Architectures with Meta Learning ICLR 2020 Complexities in Projection-Free Stochastic Non-convex Minimization AISTATS 2019 Confidence Weighted Multitask Learning AAAI 2019 Decentralized Optimization with Edge Sampling IJCAI 2019 Graph Convolutional Networks for Temporal Action Localization ICCV 2019 Hyperparameter Learning via Distributional Transfer NeurIPS 2019 Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies IJCAI 2019 NAT: Neural Architecture Transformer for Accurate and Compact Architectures NeurIPS 2019 Bandit Online Learning on Graphs via Adaptive Optimization IJCAI 2018 High-dimensional Similarity Learning via Dual-sparse Random Projection IJCAI 2018 Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication ICML 2018 Learning User Dependencies for Recommendation IJCAI 2017 Locally Linear Factorization Machines IJCAI 2017 Online Multitask Relative Similarity Learning IJCAI 2017 Projection-free Distributed Online Learning in Networks ICML 2017 Cost Sensitive Online Multiple Kernel Classification ACML 2016 Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data EMNLP 2016 Large Scale Online Kernel Learning JMLR 2016 Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization ICML 2016 A Boosting Algorithm for Item Recommendation with Implicit Feedback IJCAI 2015 Adaptive Stochastic Alternating Direction Method of Multipliers ICML 2015 Online Learning to Rank for Content-Based Image Retrieval IJCAI 2015 Stochastic Optimization with Importance Sampling for Regularized Loss Minimization ICML 2015 LIBOL: A Library for Online Learning Algorithms JMLR 2014 Online Passive Aggressive Active Learning and Its Applications ACML 2014 Large Scale Online Kernel Classification IJCAI 2013 Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection AISTATS 2011 Double Updating Online Learning JMLR 2011 DUOL: A Double Updating Approach for Online Learning NeurIPS 2009