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← Authors

Xiaorui Liu

20 papers · 2020–2025 · 7 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+11 more ↓ 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (5)
🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (7) 🤝 Dynamic Duo (10) 👑 Triple Crown 🏆 Grand Slam 🔥 Unstoppable (6) 💎 Century Club (20) ⚡ Prolific Year (6) ❓ The Questioner 🗃️ Keyword Collector (52)

Conferences

ICML (6) ICLR (5) NIPS (5) AAAI (1) AACL (1) AISTATS (1) IJCNLP (1)

Top co-authors

Jiliang Tang (10) MohamadAli Torkamani (5) Zhichao Hou (5) Yao Ma (4) Haoyu Han (4) Ming Yan (3) Neil Shah (3) Xiangyu Zhao (3) Hui LIU (3) Han Xu (3)

Keywords

graph neural network (7) adversarial robustness (4) adversarial attack (2) large language model (2) efficient inference (2) representation learning (2) sequential recommendation (2) semi-supervised learning (2) message passing (2) graph structure (1) adversarial training (1) certified robustness (1) stochastic gradient descent (1) distributed learning (1) hierarchical structure (1) robust statistics (1) communication efficiency (1) alternating optimization (1) graph representation learning (1) multi-view learning (1)

Papers

Robustness Reprogramming for Representation Learning ICLR 2025 Harnessing Robust Statistics for Trustworthy AI AAAI 2025 Rethinking Large Language Model Architectures for Sequential Recommendations AACL 2025 Rethinking Large Language Model Architectures for Sequential Recommendations IJCNLP 2025 Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks ICML 2025 Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization ICML 2025 Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing NIPS 2024 Robust Graph Neural Networks via Unbiased Aggregation NIPS 2024 ProTransformer: Robustify Transformers via Plug-and-Play Paradigm NIPS 2024 Structural Fairness-aware Active Learning for Graph Neural Networks ICLR 2024 LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation ICML 2023 Alternately Optimized Graph Neural Networks ICML 2023 Towards Label Position Bias in Graph Neural Networks NIPS 2023 Automated Self-Supervised Learning for Graphs ICLR 2022 Is Homophily a Necessity for Graph Neural Networks? ICLR 2022 To be Robust or to be Fair: Towards Fairness in Adversarial Training ICML 2021 Elastic Graph Neural Networks ICML 2021 Graph Neural Networks with Adaptive Residual NIPS 2021 Linear Convergent Decentralized Optimization with Compression ICLR 2021 A Double Residual Compression Algorithm for Efficient Distributed Learning AISTATS 2020