Xinyang Chen

17 papers · 2019–2026 · 8 conferences · across top CS/AI conferences

Achievements

+8 more ↓

🌍 Conference Polyglot (7) 🏃 Academic Marathon (6) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (14)

🌈 Renaissance Researcher (6) 🗺️ Taxonomy Completionist (35) 🧭 Keyword Pioneer 🏆 Keyword Champion (2) 🏆 Grand Slam 🗃️ Keyword Collector (71) 💎 Century Club (14) ⚡ Prolific Year (5)

Conferences

AAAI (4) ICML (4) NIPS (4) ACL (1) CVPR (1) ICCV (1) ICLR (1) IJCAI (1)

Top co-authors

Xiucheng Li (6) Mingsheng Long (5) Jianmin Wang (5) Liqiang Nie (4) Sinan Wang (4) Weili Guan (4) Xuefeng Bai (3) Yang Shu (3) Kehai Chen (2) Yu Sun (2)

Keywords

transfer learning (4) domain adaptation (3) adversarial learning (3) representation learning (3) time series forecasting (2) singular value decomposition (2) multivariate time series (2) curriculum learning (2) pseudo labeling (1) cross-modal learning (1) medical imaging (1) noisy label learning (1) label noise (1) fine-grained classification (1) model selection (1) time series classification (1) adversarial domain adaptation (1) matrix factorization (1) feature representation (1) progressive learning (1)

Papers

SAT: Balancing Reasoning Accuracy and Efficiency with Stepwise Adaptive Thinking ACL 2026 XLinear: A Lightweight and Accurate MLP-Based Model for Long-Term Time Series Forecasting with Exogenous Inputs AAAI 2026 Mitigating Endogenous Confirmation Bias in Noisy Label Learning for Vision-Language Models AAAI 2026 Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin ICML 2025 Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales AAAI 2025 Assessing Pre-Trained Models for Transfer Learning Through Distribution of Spectral Components AAAI 2025 Debiased Curriculum Adaptation for Safe Transfer Learning in Chest X-ray Classification ICCV 2025 A Survey on the Feedback Mechanism of LLM-based AI Agents IJCAI 2025 Frequency-aware Generative Models for Multivariate Time Series Imputation NIPS 2024 Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics NIPS 2024 Boosting Transferability and Discriminability for Time Series Domain Adaptation NIPS 2024 Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment ICML 2024 X-model: Improving Data Efficiency in Deep Learning with A Minimax Model ICLR 2022 Representation Subspace Distance for Domain Adaptation Regression ICML 2021 Progressive Adversarial Networks for Fine-Grained Domain Adaptation CVPR 2020 Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation ICML 2019 Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning NIPS 2019