| 2025 | Diffusion Models for Recommender Systems: From Content Distribution To Content Creation. | Jianghao Lin, Yang Cao, Yong Yu, Weinan Zhang |
| 2025 | When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark. | Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Yada Zhu, Julian Shun |
| 2025 | ScIRGen: Synthesize Realistic and Large-Scale RAG Dataset for Scientific Research. | Junyong Lin, Lu Dai, Ruiqian Han, Yijie Sui, Ruilin Wang, Xingliang Sun, Qinglin Wu, Min Feng, Hao Liu, Hui Xiong |
| 2025 | Learn to Refine: Synergistic Multi-Agent Path Optimization for Lifelong Conflict-Free Navigation of Autonomous Vehicles. | Junjun Li, Zeyuan Ma, Ting Huang, Yue-Jiao Gong |
| 2025 | Contrastive Learning for Inventory Add Prediction at Fliggy. | Manwei Li, Detao Lv, Yao Yu, Zihao Jiao |
| 2025 | GNN-SKAN: Advancing Molecular Representation Learning with SwallowKAN. | Ruifeng Li, Mingqian Li, Wei Liu, Hongyang Chen |
| 2025 | Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective. | Gaotang Li, Danai Koutra, Yujun Yan |
| 2025 | MGS3: A Multi-Granularity Self-Supervised Code Search Framework. | Rui Li, Junfeng Kang, Qi Liu, Liyang He, Zheng Zhang, Yunhao Sha, Linbo Zhu, Zhenya Huang |
| 2025 | Refining Labeling Functions with Limited Labeled Data. | Chenjie Li, Amir Gilad, Boris Glavic, Zhengjie Miao, Sudeepa Roy |
| 2025 | APEX | Zihao Li, Dongqi Fu, Mengting Ai, Jingrui He |
| 2025 | Detecting Interference using Dyadic Data in Online Controlled Experiments. | Yilin Li, Lu Deng, Yong Wang |
| 2025 | Untitled record | Lichi Li, Zain ul Abi Din, Zhen Tan, Sam London, Tianlong Chen, Ajay H. Daptardar |
| 2025 | Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective. | Ouxiang Li, Jiayin Cai, Yanbin Hao, Xiaolong Jiang, Yao Hu, Fuli Feng |
| 2025 | Unveiling Mode Connectivity in Graph Neural Network. | Bingheng Li, Zhikai Chen, Haoyu Han, Shenglai Zeng, Jingzhe Liu, Jiliang Tang |
| 2025 | Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning. | Qi Li, Zhiguang Cao, Yining Ma, Yaoxin Wu, Yue-Jiao Gong |
| 2025 | Learnable Prompt as Pseudo-Imputation: Rethinking the Necessity of Traditional EHR Data Imputation in Downstream Clinical Prediction. | Weibin Liao, Yinghao Zhu, Zhongji Zhang, Yuhang Wang, Zixiang Wang, Xu Chu, Yasha Wang, Liantao Ma |
| 2025 | Adaptive Conformal Prediction Intervals for Invariant Learning. | Shuxin Liang, Yihan Xiao, Linglong Kong, Wenlu Tang |
| 2025 | Feature Reconstruction for Anomaly Detection on Directed Multigraphs: A Preprocessing Framework for GNNs. | Sicheng Liang, Qinlin Xie, Jingqi Feng, Yiwen Yue, Hongyi Li, Jiawei Ye, Jie Wu |
| 2025 | DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting. | Daojun Liang |
| 2025 | Hexagon-Net: Heterogeneous Cross-View Aligned Graph Attention Networks for Implied Volatility Surface Prediction. | Kaiwei Liang, Ruirui Liu, Huichou Huang, Johannes Ruf, Peilin Zhao, Qingyao Wu |
| 2025 | Imputation via Domain Adaptation: Rethinking Variable Subset Forecasting from Knowledge Transfer. | Runchang Liang, Qi Hao, Yue Gao, Kunpeng Liu, Lu Jiang, Pengyang Wang, Minghao Yin |
| 2025 | Causal-aware Graph Neural Architecture Search under Distribution Shifts. | Peiwen Li, Xin Wang, Zeyang Zhang, Ziwei Zhang, Fang Shen, Jialong Wang, Yang Li, Wenwu Zhu |
| 2025 | Advancing Molecular Graph-Text Pre-training via Fine-grained Alignment. | Yibo Li, Yuan Fang, Mengmei Zhang, Chuan Shi |
| 2025 | LiPM: Foundation Model for Lithium-Ion Battery Analysis. | Juren Li, Yang Yang, Hanchen Su, Jiayu Liu, Youmin Chen, Jianfeng Zhang, Lujia Pan |
| 2025 | Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening. | Guoming Li, Jian Yang, Yifan Chen |