Xixun Lin

According to our database, Xixun Lin authored at least 59 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification.

Xixun Lin, Zhiheng Zhou, Zhengyin Zhang, Yancheng Chen, Shuai Zhang, Ge Zhang, Shichao Zhu, Lixin Zou, Chuan Zhou, Peng Zhang, Shirui Pan, Yanan Cao

CoRR, May, 2026

SafeHarness: Lifecycle-Integrated Security Architecture for LLM-based Agent Deployment.

Xixun Lin, Yang Liu, Yancheng Chen, Yongxuan Wu, Yucheng Ning, Yilong Liu, Nan Sun, Shun Zhang, Bin Chong, Chuan Zhou, Yanan Cao, Li Guo

CoRR, April, 2026

CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems.

Yongxuan Wu, Xixun Lin, He Zhang, Nan Sun, Kun Wang, Chuan Zhou, Shirui Pan, Yanan Cao

CoRR, April, 2026

EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment.

Yixuan Nan, Xixun Lin, Yanmin Shang, Ge Zhang, Zheng Fang, Fang Fang, Yanan Cao

CoRR, April, 2026

Do LLMs Know Tool Irrelevance? Demystifying Structural Alignment Bias in Tool Invocations.

Yilong Liu, Xixun Lin, Pengfei Cao, Ge Zhang, Fang Fang, Yanan Cao

CoRR, April, 2026

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing.

Zhiheng Zhou, Mengyao Zhou, Xixun Lin, Xingqin Qi, Guiying Yan

CoRR, April, 2026

D2TCDR: Disentangled Diffusion-Based Transfer for Cross-Domain Recommendation.

Hong Zhou, Xixun Lin, Yanan Cao, Shichao Zhu, Renqi Jia, Xiangyu Zhao, Guandong Xu, Li Guo

ACM Trans. Inf. Syst., March, 2026

Erratum: Learning Discrete Identifiers and Dense Vectors for Generative Retrieval.

Yunfan Xie, Lixin Zou, Xiangyang Luo, Hengyi Cai, Chaoran Zhang, Liming Dong, Xixun Lin, Chenliang Li

ACM Trans. Inf. Syst., March, 2026

Learning Discrete Identifiers and Dense Vectors for Generative Retrieval.

Yunfan Xie, Lixin Zou, Xiangyang Luo, Hengyi Cai, Chaoran Zhang, Liming Dong, Xixun Lin, Chenliang Li

ACM Trans. Inf. Syst., February, 2026

Hard Constraints Meet Soft Generation: Guaranteed Feasibility for LLM-based Combinatorial Optimization.

Yang Liu, Chuan Zhou, Yancheng Chen, Shuai Zhang, Xixun Lin, Xiaoqing Wang

CoRR, February, 2026

Generative Causality-Driven Network for Graph Multi-Task Learning.

Xixun Lin, Qing Yu, Yanan Cao, Lixin Zou, Chuan Zhou, Jia Wu, Chenliang Li, Peng Zhang, Shirui Pan

IEEE Trans. Pattern Anal. Mach. Intell., January, 2026

MuVaC: AVariational Causal Framework for Multimodal Sarcasm Understanding in Dialogues.

Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu

CoRR, January, 2026

Learning Subgraph-Based Normality for Interpretable Graph-Level Anomaly Detection.

Ge Zhang, Zhenyu Yang, Jia Wu, Pengfei Jiao, Jian Yang, Hao Peng, Xixun Lin

IEEE Trans. Inf. Forensics Secur., 2026

Generalizable Graph-level Anomaly Detection via Prompted Anomaly Expansion and Normality Extraction.

Ge Zhang, Jiapei Chen, Guohao Sun, Xiu Fang, Zhenyu Yang, Xixun Lin, Liang Yang

Proceedings of the ACM Web Conference 2026, 2026

Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion.

Jiawei Sheng, Taoyu Su, Xixun Lin, Xiaodong Li, Tingwen Liu

Proceedings of the ACM Web Conference 2026, 2026

Scaling Collaborative Filtering with Multimodal Contrastive Fine-tuning.

Liwei Jin, Dan Luo, Lixin Zou, Chenliang Li, Xiangyang Luo, Xixun Lin, Liming Dong, Yifan Zhang

Proceedings of the ACM Web Conference 2026, 2026

MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues.

Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu

Proceedings of the ACM Web Conference 2026, 2026

Breaking One-Size-Fits-All: Revisiting Out-of-Distribution Detection on Graphs Under Diverse Distribution Shifts.

Chuancheng Song, Hanyang Shen, Yan Dong, Xixun Lin, Yanmin Shang, Yanan Cao

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

PathMind: A Retrieve-Prioritize-Reason Framework for Knowledge Graph Reasoning with Large Language Models.

Yu Liu, Xixun Lin, Yanmin Shang, Yangxi Li, Shi Wang, Yanan Cao

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

V-ITI: Mitigating Hallucinations in Multimodal Large Language Models via Visual Inference-Time Intervention.

Nan Sun, Zhenyu Zhang, Xixun Lin, Kun Wang, Yanmin Shang, Naibin Gu, Shuohuan Wang, Yu Sun, Hua Wu, Haifeng Wang, Yanan Cao

CoRR, December, 2025

MAD-Fact: A Multi-Agent Debate Framework for Long-Form Factuality Evaluation in LLMs.

Yucheng Ning, Xixun Lin, Fang Fang, Yanan Cao

CoRR, October, 2025

LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions.

Xixun Lin, Yucheng Ning, Jingwen Zhang, Yan Dong, Yilong Liu, Yongxuan Wu, Xiaohua Qi, Nan Sun, Yanmin Shang, Pengfei Cao, Lixin Zou, Xu Chen, Chuan Zhou, Jia Wu, Shirui Pan, Bin Wang, Yanan Cao, Kai Chen, Songlin Hu, Li Guo

CoRR, September, 2025

LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation.

Yang Sun, Lixin Zou, Dan Luo, Zhiyong Xie, Long Zhang, Liming Dong, Yunwei Zhao, Xixun Lin, Yanxiong Lu, Chenliang Li

CoRR, August, 2025

Contrastive Modality-Disentangled Learning for Multimodal Recommendation.

Xixun Lin, Rui Liu, Yanan Cao, Lixin Zou, Qian Li, Yongxuan Wu, Yang Liu, Dawei Yin, Guandong Xu

ACM Trans. Inf. Syst., May, 2025

Large Language Models for Planning: A Comprehensive and Systematic Survey.

Pengfei Cao, Tianyi Men, Wencan Liu, Jingwen Zhang, Xuzhao Li, Xixun Lin, Dianbo Sui, Yanan Cao, Kang Liu, Jun Zhao

CoRR, May, 2025

BadMoE: Backdooring Mixture-of-Experts LLMs via Optimizing Routing Triggers and Infecting Dormant Experts.

Qingyue Wang, Qi Pang, Xixun Lin, Shuai Wang, Daoyuan Wu

CoRR, April, 2025

A data-centric framework of improving graph neural networks for knowledge graph embedding.

Yanan Cao, Xixun Lin, Yongxuan Wu, Fengzhao Shi, Yanmin Shang, Qingfeng Tan, Chuan Zhou, Peng Zhang

World Wide Web (WWW), January, 2025

Equivariant Hypergraph Diffusion for Crystal Structure Prediction.

Yang Liu, Chuan Zhou, Shuai Zhang, Peng Zhang, Xixun Lin, Shirui Pan

CoRR, January, 2025

IBPL: Information Bottleneck-based Prompt Learning for graph out-of-distribution detection.

Yanan Cao, Fengzhao Shi, Qing Yu, Xixun Lin, Chuan Zhou, Lixin Zou, Peng Zhang, Zhao Li, Dawei Yin

Neural Networks, 2025

Conformal Graph-level Out-of-distribution Detection with Adaptive Data Augmentation.

Xixun Lin, Yanan Cao, Nan Sun, Lixin Zou, Chuan Zhou, Peng Zhang, Shuai Zhang, Ge Zhang, Jia Wu

Proceedings of the ACM on Web Conference 2025, 2025

Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs.

Nan Sun, Xixun Lin, Zhiheng Zhou, Yanmin Shang, Zhenlin Cheng, Yanan Cao

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

Deep Graph Neural Point Process for Learning Temporal Interactive Networks.

Su Chen, Xiaohua Qi, Xixun Lin, Yanmin Shang, Xiaolin Xu, Yangxi Li

Proceedings of the Natural Language Processing and Chinese Computing, 2025

TTGL: Large-scale Multi-scenario Universal Graph Learning at TikTok.

Shichao Zhu, Mufan Li, Guangmou Pan, Xixun Lin

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

FairCDR: Transferring Fairness and User Preferences for Cross-Domain Recommendation.

Yongxuan Wu, Yang Liu, Xixun Lin, Hong Zhou, Yanan Cao, Lixin Zou, Yanmin Shang, Yanbing Liu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Conformal Anomaly Detection in Event Sequences.

Shuai Zhang, Chuan Zhou, Yang Liu, Peng Zhang, Xixun Lin, Shirui Pan

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Federated Privacy-Preserving for Cross-Domain Sequential Recommendation.

Su Chen, Yan Dong, Yanmin Shang, Xiaolin Xu, Xixun Lin

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2025, 2025

Enhancing Large Language Model for Knowledge Graph Completion via Structure-Aware Alignment-Tuning.

Yu Liu, Yanan Cao, Xixun Lin, Yanmin Shang, Shi Wang, Shirui Pan

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

RANA: Robust Active Learning for Noisy Network Alignment.

Yixuan Nan, Xixun Lin, Yanmin Shang, Zhuofan Li, Can Zhao, Yanan Cao

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

Reliably Bounding False Positives: A Zero-Shot Machine-Generated Text Detection Framework via Multiscaled Conformal Prediction.

Xiaowei Zhu, Yubing Ren, Yanan Cao, Xixun Lin, Fang Fang, Yangxi Li

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

UniFORM: Towards Unified Framework for Anomaly Detection on Graphs.

Chuancheng Song, Xixun Lin, Hanyang Shen, Yanmin Shang, Yanan Cao

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

VR-GNN: variational relation vector graph neural network for modeling homophily and heterophily.

Fengzhao Shi, Yanan Cao, Ren Li, Xixun Lin, Yanmin Shang, Chuan Zhou, Jia Wu, Shirui Pan

World Wide Web (WWW), May, 2024

Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification.

Xixun Lin, Zhao Li, Peng Zhang, Luchen Liu, Chuan Zhou, Bin Wang, Zhihong Tian

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation.

Xixun Lin, Chuan Zhou, Jia Wu, Lixin Zou, Shirui Pan, Yanan Cao, Bin Wang, Shuaiqiang Wang, Dawei Yin

IEEE Trans. Knowl. Data Eng., April, 2024

Neural Jump-Diffusion Temporal Point Processes.

Shuai Zhang, Chuan Zhou, Yang Aron Liu, Peng Zhang, Xixun Lin, Zhi-Ming Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification.

Xixun Lin, Wenxiao Zhang, Fengzhao Shi, Chuan Zhou, Lixin Zou, Xiangyu Zhao, Dawei Yin, Shirui Pan, Yanan Cao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

CL4CO: A Curriculum Training Framework for Graph-Based Neural Combinatorial Optimization.

Yang Liu, Chuan Zhou, Peng Zhang, Zhao Li, Shuai Zhang, Xixun Lin, Xindong Wu

Proceedings of the IEEE International Conference on Data Mining, 2024

2023

Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification.

Xixun Lin, Chuan Zhou, Jia Wu, Hong Yang, Haibo Wang, Yanan Cao, Bin Wang

Pattern Recognit., 2023

2022

DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation.

Jiangxia Cao, Xixun Lin, Xin Cong, Jing Ya, Tingwen Liu, Bin Wang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Learning Common Dependency Structure for Unsupervised Cross-Domain Ner.

Luchen Liu, Xixun Lin, Peng Zhang, Lei Zhang, Bin Wang

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Task-adaptive Neural Process for User Cold-Start Recommendation.

Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, Bin Wang

Proceedings of the WWW '21: The Web Conference 2021, 2021

Bipartite Graph Embedding via Mutual Information Maximization.

Jiangxia Cao, Xixun Lin, Shu Guo, Luchen Liu, Tingwen Liu, Bin Wang

Proceedings of the WSDM '21, 2021

Deep Structural Point Process for Learning Temporal Interaction Networks.

Jiangxia Cao, Xixun Lin, Xin Cong, Shu Guo, Hengzhu Tang, Tingwen Liu, Bin Wang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences.

Xixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, Bin Wang

Proceedings of the IEEE International Conference on Data Mining, 2021

Improving Cross-Domain Slot Filling with Common Syntactic Structure.

Luchen Liu, Xixun Lin, Peng Zhang, Bin Wang

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Exploratory Adversarial Attacks on Graph Neural Networks.

Xixun Lin, Chuan Zhou, Hong Yang, Jia Wu, Haibo Wang, Yanan Cao, Bin Wang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Relation path embedding in knowledge graphs.

Xixun Lin, Yanchun Liang, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan

Neural Comput. Appl., 2019

Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding.

Xixun Lin, Hong Yang, Jia Wu, Chuan Zhou, Bin Wang

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

A Knowledge Base Completion Model Based on Path Feature Learning.

Xixun Lin, Yanchun Liang, Limin Wang, Xu Wang, Mary Qu Yang, Renchu Guan

Int. J. Comput. Commun. Control, 2018

2016

Compositional Learning of Relation Paths Embedding for Knowledge Base Completion.

Xixun Lin, Yanchun Liang, Renchu Guan

CoRR, 2016