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← Authors

Muhan Zhang

48 papers · 2018–2026 · 6 conferences · across top CS/AI conferences

Achievements

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+14 more ↓ 🌍 Conference Polyglot (6) 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (14)
🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (6) 🤝 Dynamic Duo (13) 👑 Triple Crown 👥 Mega-Team (20) 🔬 Deep Specialist (16) 🧬 Topic Evolution 🏆 Keyword Champion (2) 🗃️ Keyword Collector (99) ⚡ Prolific Year (8) 🔥 Unstoppable (8) 💎 Century Club (44) ❓ The Questioner (3)

Conferences

NIPS (17) ICLR (13) ICML (10) ACL (6) EMNLP (1) JMLR (1)

Top co-authors

Xiyuan Wang (13) Yixin Chen (12) Jiarui Feng (6) Pan Li (6) Lecheng Kong (5) Fuhai Li (4) Cai Zhou (4) Yinan Huang (4) Dacheng Tao (4) Hao Liu (4)

Research topics

Understanding (1)

Keywords

graph neural network (16) message passing (6) graph isomorphism (4) link prediction (4) reinforcement learning (4) representation learning (3) large language model (3) node classification (3) message passing neural network (2) latent space (2) directed acyclic graph (2) low-rank adaptation (2) parameter-efficient fine-tuning (2) subgraph extraction (2) model compression (2) expressive power (2) weisfeiler-lehman test (2) neural architecture search (2) variational autoencoder (2) inductive reasoning (1)

Papers

Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation ACL 2026 JurisBench: A Deep Benchmark for Assessing Large Language Models in Professional Legal Practice ACL 2026 SubTokenTest: A Practical Benchmark for Real-World Sub-token Understanding ACL 2026 Towards a Mechanistic Understanding of Large Reasoning Models: A Survey of Training, Inference, and Failures ACL 2026 Geometric Representation Condition Improves Equivariant Molecule Generation ICML 2025 GOFA: A Generative One-For-All Model for Joint Graph Language Modeling ICLR 2025 Number Cookbook: Number Understanding of Language Models and How to Improve It ICLR 2025 HD-PiSSA: High-Rank Distributed Orthogonal Adaptation EMNLP 2025 On the Completeness of Invariant Geometric Deep Learning Models ICLR 2025 Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick JMLR 2025 Griffin: Towards a Graph-Centric Relational Database Foundation Model ICML 2025 CLOVER: Cross-Layer Orthogonal Vectors Pruning ICML 2025 RulE: Knowledge Graph Reasoning with Rule Embedding ACL 2024 Mars: Situated Inductive Reasoning in an Open-World Environment NIPS 2024 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs NIPS 2024 Unifying Generation and Prediction on Graphs with Latent Graph Diffusion NIPS 2024 PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models NIPS 2024 LooGLE: Can Long-Context Language Models Understand Long Contexts? ACL 2024 Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability ICLR 2024 On the Stability of Expressive Positional Encodings for Graphs ICLR 2024 Neural Common Neighbor with Completion for Link Prediction ICLR 2024 One For All: Towards Training One Graph Model For All Classification Tasks ICLR 2024 VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs ICLR 2024 Case-Based or Rule-Based: How Do Transformers Do the Math? ICML 2024 Graph As Point Set ICML 2024 An Empirical Study of Realized GNN Expressiveness ICML 2024 Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes NIPS 2023 Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power NIPS 2023 From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks ICML 2023 Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs ICLR 2023 CktGNN: Circuit Graph Neural Network for Electronic Design Automation ICLR 2023 Is Distance Matrix Enough for Geometric Deep Learning? NIPS 2023 MAG-GNN: Reinforcement Learning Boosted Graph Neural Network NIPS 2023 Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman NIPS 2023 Rethinking Knowledge Graph Evaluation Under the Open-World Assumption NIPS 2022 Geodesic Graph Neural Network for Efficient Graph Representation Learning NIPS 2022 How Powerful are K-hop Message Passing Graph Neural Networks NIPS 2022 PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs ICML 2022 3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design ICML 2022 How Powerful are Spectral Graph Neural Networks ICML 2022 GLASS: GNN with Labeling Tricks for Subgraph Representation Learning ICLR 2022 Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks ICLR 2022 Nested Graph Neural Networks NIPS 2021 Decoupling the Depth and Scope of Graph Neural Networks NIPS 2021 Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning NIPS 2021 Inductive Matrix Completion Based on Graph Neural Networks ICLR 2020 D-VAE: A Variational Autoencoder for Directed Acyclic Graphs NIPS 2019 Link Prediction Based on Graph Neural Networks NIPS 2018