Shirui Pan

CARD: Towards Conditional Design of Multi-agent Topological Structures

CDTP: A Large-Scale Chinese Data-Text Pair Dataset for Comprehensive Evaluation of Chinese LLMs

The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge

Knowledge Reasoning Language Model: Unifying Knowledge and Language for Inductive Knowledge Graph Reasoning

Paradigm Shift of GNN Explainer from Label Space to Prototypical Representation Space

TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models

Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting

Lightweight Graph-Free Condensation with MLP-Driven Optimization

Estimating Time Series Foundation Model Transferability via In-Context Learning

Conformal Anomaly Detection in Event Sequences

GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation

ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models

Graph Sparsification via Mixture of Graphs

Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective

Equivalence is All: A Unified View for Self-supervised Graph Learning

DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs

Unsupervised Federated Graph Learning

Test-Time Graph Neural Dataset Search With Generative Projection

BiMark: Unbiased Multilayer Watermarking for Large Language Models

N2GON: Neural Networks for Graph-of-Net with Position Awareness

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark

Towards Neural Scaling Laws for Time Series Foundation Models

TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting

Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification

Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

GraphSTAGE: Channel-Preserving Graph Neural Networks for Time Series Forecasting

MPHIL: Multi-Prototype Hyperspherical Invariant Learning for Graph Out-of-Distribution Generalization

Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

Test-Time Graph Rebirth: Serving GNN Generalization Under Distribution Shifts

Benchmarks and Custom Package for Energy Forecasting

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

ChemThinker: Thinking Like a Chemist with Multi-Agent LLMs for Deep Molecular Insights