Shuiwang Ji

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents ACL 2026 DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra ICML 2025 Discovering Physics Laws of Dynamical Systems via Invariant Function Learning ICML 2025 EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association ACL 2025 Eliminating Position Bias of Language Models: A Mechanistic Approach ICLR 2025 Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models ICLR 2025 Geometry Informed Tokenization of Molecules for Language Model Generation ICML 2025 Learning to Discover Regulatory Elements for Gene Expression Prediction ICLR 2025 On Explaining Equivariant Graph Networks via Improved Relevance Propagation ICML 2025 Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning ACL 2025 Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design ICML 2025 A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery EMNLP 2024 Active Test-Time Adaptation: Theoretical Analyses and An Algorithm ICLR 2024 A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction ICML 2024 Complete and Efficient Graph Transformers for Crystal Material Property Prediction ICLR 2024 Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency ICML 2024 Graph Structure Extrapolation for Out-of-Distribution Generalization ICML 2024 Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation NeurIPS 2024 On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods ICLR 2024 Position: TrustLLM: Trustworthiness in Large Language Models ICML 2024 SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations ICLR 2024 A new perspective on building efficient and expressive 3D equivariant graph neural networks NeurIPS 2023 Automated Data Augmentations for Graph Classification ICLR 2023 Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian ICML 2023 Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction ICML 2023 Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models ICLR 2023 Graph Mixup with Soft Alignments ICML 2023 Group Equivariant Fourier Neural Operators for Partial Differential Equations ICML 2023 Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization NeurIPS 2023 Learning Fair Graph Representations via Automated Data Augmentations ICLR 2023 Learning Hierarchical Protein Representations via Complete 3D Graph Networks ICLR 2023 QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules NeurIPS 2023 Towards Symmetry-Aware Generation of Periodic Materials NeurIPS 2023 Video Timeline Modeling For News Story Understanding NeurIPS 2023 An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch ICLR 2022 ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs NeurIPS 2022 Generating 3D Molecules for Target Protein Binding ICML 2022 GOOD: A Graph Out-of-Distribution Benchmark NeurIPS 2022 GraphFM: Improving Large-Scale GNN Training via Feature Momentum ICML 2022 Periodic Graph Transformers for Crystal Material Property Prediction NeurIPS 2022 Self-Supervised Representation Learning via Latent Graph Prediction ICML 2022 Spherical Message Passing for 3D Molecular Graphs ICLR 2022 Task-Agnostic Graph Explanations NeurIPS 2022 ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs NeurIPS 2021 DIG: A Turnkey Library for Diving into Graph Deep Learning Research JMLR 2021 GraphDF: A Discrete Flow Model for Molecular Graph Generation ICML 2021 On Explainability of Graph Neural Networks via Subgraph Explorations ICML 2021 Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence NeurIPS 2021 Adaptive Convolutional ReLUs AAAI 2020 A Multi-Scale Approach for Graph Link Prediction AAAI 2020 Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising NeurIPS 2020 Non-Local U-Nets for Biomedical Image Segmentation AAAI 2020 StructPool: Structured Graph Pooling via Conditional Random Fields ICLR 2020 Dense Transformer Networks for Brain Electron Microscopy Image Segmentation IJCAI 2019 Graph U-Nets ICML 2019 Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods AAAI 2019 ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions NeurIPS 2018 Multi-class Discriminant Kernel Learning via Convex Programming JMLR 2008 Multi-label Multiple Kernel Learning NeurIPS 2008