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ORCIDJiliang Tang
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- affiliation: Michigan State University, East Lansing, MI, USA
- affiliation (Ph.D.): Arizona State University, Tempe, Arizona, USA
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2020 – today
- 2024
[j44]Dylan Molho
, Jiayuan Ding, Wenzhuo Tang, Zhaoheng Li, Hongzhi Wen, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang:
Deep Learning in Single-cell Analysis. ACM Trans. Intell. Syst. Technol. 15(3): 40:1-40:62 (2024)- [c230]Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin:
Exploring Memorization in Fine-tuned Language Models. ACL (1) 2024: 3917-3948 - [c229]Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). ACL (Findings) 2024: 4505-4524 - [c228]Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu:
Content Knowledge Identification with Multi-agent Large Language Models (LLMs). AIED (2) 2024: 284-292 - [c227]Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang:
Label-free Node Classification on Graphs with Large Language Models (LLMs). ICLR 2024 - [c226]Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada:
Structural Fairness-aware Active Learning for Graph Neural Networks. ICLR 2024 - [c225]Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang:
Sharpness-Aware Data Poisoning Attack. ICLR 2024 - [c224]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: a data perspective. ICLR 2024 - [c223]Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang:
CellPLM: Pre-training of Cell Language Model Beyond Single Cells. ICLR 2024 - [c222]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c221]Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin:
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. ICML 2024 - [c220]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao, Qian Chen, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. ICML 2024 - [c219]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Position: Graph Foundation Models Are Already Here. ICML 2024 - [c218]Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang:
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. KDD 2024: 932-943 - [c217]Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang:
LPFormer: An Adaptive Graph Transformer for Link Prediction. KDD 2024: 2686-2698 - [c216]Qingsong Wen, Jing Liang, Carles Sierra, Rose Luckin, Richard Jiarui Tong, Zitao Liu, Peng Cui, Jiliang Tang:
AI for Education (AI4EDU): Advancing Personalized Education with LLM and Adaptive Learning. KDD 2024: 6743-6744 - [c215]Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang:
A Robust Semantics-based Watermark for Large Language Model against Paraphrasing. NAACL-HLT (Findings) 2024: 613-625 - [c214]Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li:
Masked Graph Autoencoder with Non-discrete Bandwidths. WWW 2024: 377-388 - [c213]Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin:
Whole Page Unbiased Learning to Rank. WWW 2024: 1431-1440 - [c212]Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang:
The 1st International Workshop on Graph Foundation Models (GFM). WWW (Companion Volume) 2024: 1789-1792 - [i173]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i172]Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing:
Superiority of Multi-Head Attention in In-Context Linear Regression. CoRR abs/2401.17426 (2024) - [i171]Jingzhe Liu, Haitao Mao, Zhikai Chen, Tong Zhao, Neil Shah, Jiliang Tang:
Neural Scaling Laws on Graphs. CoRR abs/2402.02054 (2024) - [i170]Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang:
Data Poisoning for In-context Learning. CoRR abs/2402.02160 (2024) - [i169]Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang:
A Data Generation Perspective to the Mechanism of In-Context Learning. CoRR abs/2402.02212 (2024) - [i168]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Graph Foundation Models. CoRR abs/2402.02216 (2024) - [i167]Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang:
Copyright Protection in Generative AI: A Technical Perspective. CoRR abs/2402.02333 (2024) - [i166]Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li:
Masked Graph Autoencoder with Non-discrete Bandwidths. CoRR abs/2402.03814 (2024) - [i165]Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin:
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective. CoRR abs/2402.04621 (2024) - [i164]Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang:
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. CoRR abs/2402.08228 (2024) - [i163]Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang:
Mixture of Link Predictors. CoRR abs/2402.08583 (2024) - [i162]Juanhui Li, Haoyu Han, Zhikai Chen, Harry Shomer, Wei Jin, Amin Javari, Jiliang Tang:
Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation. CoRR abs/2402.08921 (2024) - [i161]Hanbing Wang, Xiaorui Liu, Wenqi Fan, Xiangyu Zhao, Venkataramana Kini, Devendra Yadav, Fei Wang, Zhen Wen, Jiliang Tang, Hui Liu:
Rethinking Large Language Model Architectures for Sequential Recommendations. CoRR abs/2402.09543 (2024) - [i160]Kaiqi Yang, Hang Li, Hongzhi Wen, Tai-Quan Peng, Jiliang Tang, Hui Liu:
Are Large Language Models (LLMs) Good Social Predictors? CoRR abs/2402.12620 (2024) - [i159]Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen:
Bringing Generative AI to Adaptive Learning in Education. CoRR abs/2402.14601 (2024) - [i158]Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). CoRR abs/2402.16893 (2024) - [i157]Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang:
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention. CoRR abs/2403.11052 (2024) - [i156]Hang Li, Tianlong Xu, Jiliang Tang, Qingsong Wen:
Automate Knowledge Concept Tagging on Math Questions with LLMs. CoRR abs/2403.17281 (2024) - [i155]Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen:
Large Language Models for Education: A Survey and Outlook. CoRR abs/2403.18105 (2024) - [i154]Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu:
Content Knowledge Identification with Multi-Agent Large Language Models (LLMs). CoRR abs/2404.07960 (2024) - [i153]Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang:
Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models. CoRR abs/2406.01899 (2024) - [i152]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. CoRR abs/2406.01908 (2024) - [i151]Guangliang Liu, Haitao Mao, Bochuan Cao, Zhiyu Xue, Kristen Marie Johnson, Jiliang Tang, Rongrong Wang:
On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept. CoRR abs/2406.02378 (2024) - [i150]Haoyu Han, Juanhui Li, Wei Huang, Xianfeng Tang, Hanqing Lu, Chen Luo, Hui Liu, Jiliang Tang:
Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach. CoRR abs/2406.03464 (2024) - [i149]Jay Revolinsky, Harry Shomer, Jiliang Tang:
Understanding the Generalizability of Link Predictors Under Distribution Shifts on Graphs. CoRR abs/2406.08788 (2024) - [i148]Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang:
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR abs/2406.10727 (2024) - [i147]Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang:
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. CoRR abs/2406.10794 (2024) - [i146]Harry Shomer, Jay Revolinsky, Jiliang Tang:
Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion. CoRR abs/2406.11898 (2024) - [i145]Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu:
A Pure Transformer Pretraining Framework on Text-attributed Graphs. CoRR abs/2406.13873 (2024) - [i144]Hang Li, Tianlong Xu, Jiliang Tang, Qingsong Wen:
Knowledge Tagging System on Math Questions via LLMs with Flexible Demonstration Retriever. CoRR abs/2406.13885 (2024) - [i143]Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu:
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. CoRR abs/2406.13933 (2024) - [i142]Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang:
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. CoRR abs/2406.14773 (2024) - [i141]Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu:
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. CoRR abs/2406.14855 (2024) - [i140]Kai Guo, Zewen Liu, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang:
Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. CoRR abs/2407.12068 (2024) - [i139]Guangliang Liu, Haitao Mao, Jiliang Tang, Kristen Marie Johnson:
Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis. CoRR abs/2407.15286 (2024) - [i138]Chen Luo, Xianfeng Tang, Hanqing Lu, Yaochen Xie, Hui Liu, Zhenwei Dai, Limeng Cui, Ashutosh Joshi, Sreyashi Nag, Yang Li, Zhen Li, Rahul Goutam, Jiliang Tang, Haiyang Zhang, Qi He:
Exploring Query Understanding for Amazon Product Search. CoRR abs/2408.02215 (2024) - [i137]Jinhui Pang, Zixuan Wang, Jiliang Tang, Mingyan Xiao, Nan Yin:
SA-GDA: Spectral Augmentation for Graph Domain Adaptation. CoRR abs/2408.09189 (2024) - [i136]Xinnan Dai, Qihao Wen, Yifei Shen, Hongzhi Wen, Dongsheng Li, Jiliang Tang, Caihua Shan:
Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path. CoRR abs/2408.09529 (2024) - 2023
- [j43]Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang:
Customized Graph Nerual Networks. IEEE Data Eng. Bull. 46(2): 108-125 (2023) - [j42]Xin Juan, Fengfeng Zhou, Wentao Wang, Wei Jin, Jiliang Tang, Xin Wang:
INS-GNN: Improving graph imbalance learning with self-supervision. Inf. Sci. 637: 118935 (2023) - [j41]Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang:
Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. SIGKDD Explor. 25(2): 42-61 (2023) - [j40]Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Yunhao Liu, Anil K. Jain, Jiliang Tang:
Trustworthy AI: A Computational Perspective. ACM Trans. Intell. Syst. Technol. 14(1): 4:1-4:59 (2023) - [j39]Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang:
Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles. IEEE Trans. Knowl. Data Eng. 35(12): 12415-12429 (2023) - [j38]Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu:
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering. ACM Trans. Inf. Syst. 41(2): 43:1-43:27 (2023) - [c211]Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? ACL (1) 2023: 10696-10711 - [c210]Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang:
Single-Cell Multimodal Prediction via Transformers. CIKM 2023: 2422-2431 - [c209]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. EMNLP 2023: 14692-14707 - [c208]Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. ICDE 2023: 654-667 - [c207]Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah:
Empowering Graph Representation Learning with Test-Time Graph Transformation. ICLR 2023 - [c206]Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang:
Transferable Unlearnable Examples. ICLR 2023 - [c205]Haoyu Han, Xiaorui Liu, Haitao Mao, MohamadAli Torkamani, Feng Shi, Victor Lee, Jiliang Tang:
Alternately Optimized Graph Neural Networks. ICML 2023: 12411-12429 - [c204]Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang:
Probabilistic Categorical Adversarial Attack and Adversarial Training. ICML 2023: 38428-38442 - [c203]Chengyi Liu, Wenqi Fan, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li:
Generative Diffusion Models on Graphs: Methods and Applications. IJCAI 2023: 6702-6711 - [c202]Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang:
How does the Memorization of Neural Networks Impact Adversarial Robust Models? KDD 2023: 2801-2812 - [c201]Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu:
Large-Scale Graph Neural Networks: The Past and New Frontiers. KDD 2023: 5835-5836 - [c200]Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo:
Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). KDD 2023: 5891-5892 - [c199]Jinhui Pang, Zixuan Wang, Jiliang Tang, Mingyan Xiao, Nan Yin:
SA-GDA: Spectral Augmentation for Graph Domain Adaptation. ACM Multimedia 2023: 309-318 - [c198]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS 2023 - [c197]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. NeurIPS 2023 - [c196]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. NeurIPS 2023 - [c195]Zitao Liu, Qiongqiong Liu, Teng Guo, Jiahao Chen, Shuyan Huang, Xiangyu Zhao, Jiliang Tang, Weiqi Luo, Jian Weng:
XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information. NeurIPS 2023 - [c194]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS 2023 - [c193]Juanhui Li, Wei Zeng, Suqi Cheng, Yao Ma, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. SIGIR 2023: 3315-3319 - [c192]Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang:
Toward Degree Bias in Embedding-Based Knowledge Graph Completion. WWW 2023: 705-715 - [i135]Wenqi Fan, Chengyi Liu, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li:
Generative Diffusion Models on Graphs: Methods and Applications. CoRR abs/2302.02591 (2023) - [i134]Hongzhi Wen, Wenzhuo Tang, Wei Jin, Jiayuan Ding, Renming Liu, Feng Shi, Yuying Xie, Jiliang Tang:
Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation. CoRR abs/2302.03038 (2023) - [i133]Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang:
Toward Degree Bias in Embedding-Based Knowledge Graph Completion. CoRR abs/2302.05044 (2023) - [i132]Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang:
Single-Cell Multimodal Prediction via Transformers. CoRR abs/2303.00233 (2023) - [i131]Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang:
Sharpness-Aware Data Poisoning Attack. CoRR abs/2305.14851 (2023) - [i130]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. CoRR abs/2305.15822 (2023) - [i129]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR abs/2306.01323 (2023) - [i128]Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Jiliang Tang:
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models. CoRR abs/2306.04642 (2023) - [i127]Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, Qing Li:
Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective. CoRR abs/2306.06615 (2023) - [i126]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. CoRR abs/2306.10453 (2023) - [i125]Wenqi Fan, Zihuai Zhao, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Jiliang Tang, Qing Li:
Recommender Systems in the Era of Large Language Models (LLMs). CoRR abs/2307.02046 (2023) - [i124]Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang:
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. CoRR abs/2307.03393 (2023) - [i123]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR abs/2307.09688 (2023) - [i122]Geri Skenderi, Hang Li, Jiliang Tang, Marco Cristani:
Graph-level Representation Learning with Joint-Embedding Predictive Architectures. CoRR abs/2309.16014 (2023) - [i121]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: A Data Perspective. CoRR abs/2310.00793 (2023) - [i120]Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang:
On the Generalization of Training-based ChatGPT Detection Methods. CoRR abs/2310.01307 (2023) - [i119]Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang:
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. CoRR abs/2310.02401 (2023) - [i118]Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang:
Label-free Node Classification on Graphs with Large Language Models (LLMS). CoRR abs/2310.04668 (2023) - [i117]Pengfei He, Han Xu, Yue Xing, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou:
Confidence-driven Sampling for Backdoor Attacks. CoRR abs/2310.05263 (2023) - [i116]