ResearchAlpha Leak

Conferences Topics Top Authors Rankings Browse All

Home/Authors/Peilin Zhao

Peilin Zhao

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 4:44 AM AMS

22

papers

569

total citations

papers (22)

RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist

NEURIPS 2020arXiv

GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

NEURIPS 2023arXiv

Fairness-guided Few-shot Prompting for Large Language Models

NEURIPS 2023arXiv

Test-Time Model Adaptation with Only Forward Passes

Meta-learning with an Adaptive Task Scheduler

NEURIPS 2021arXiv

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

NEURIPS 2022arXiv

Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation

Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples

SVIP: Sequence VerIfication for Procedures in Videos

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction

Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution

Learning Neural Set Functions Under the Optimal Subset Oracle

NEURIPS 2022arXiv

Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity

Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model

HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting

Latent Diffusion Transformer for Probabilistic Time Series Forecasting

Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP

NEURIPS 2025arXiv

Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition

Retaining Beneficial Information from Detrimental Data for Neural Network Repair

Adversarial Sparse Transformer for Time Series Forecasting

Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization

On the Pitfall of Mixup for Uncertainty Calibration