| 2026 | FedKDMR: Robust Federated Learning via Joint Knowledge Distillation & Model Recombination. | Wenhao Li, Christos Anagnostopoulos, Shameem A. Puthiya Parambath, Kevin Bryson |
| 2026 | Invariant Graph Transformer for Out-of-Distribution Generalization. | Tianyin Liao, Ziwei Zhang, Yufei Sun, Chunyu Hu, Jianxin Li |
| 2026 | HyFunc: Accelerating LLM-based Function Calls for Agentic AI through Hybrid-Model Cascade and Dynamic Templating. | Weibin Liao, Jian-Guang Lou, Haoyi Xiong |
| 2026 | Accelerated Coordinate Descent for Directed Densest Subgraph Discovery. | Luocheng Liang, Yingli Zhou, Yixiang Fang |
| 2026 | InfoDCL: Informative Noise Enhanced Diffusion Based Contrastive Learning. | Xufeng Liang, Zhida Qin, Chong Zhang, Tianyu Huang, Gangyi Ding |
| 2026 | Generative Large-Scale Pre-trained Models for Automated Ad Bidding Optimization. | Yu Lei, Jiayang Zhao, Yilei Zhao, Zhaoqi Zhang, Linyou Cai, Qianlong Xie, Xingxing Wang |
| 2026 | HumanLLM: Towards Personalized Understanding and Simulation of Human Nature. | Yuxuan Lei, Tianfu Wang, Jianxun Lian, Zhengyu Hu, Defu Lian, Xing Xie |
| 2026 | Offline Behavioral Data Selection. | Shiye Lei, Zhihao Cheng, Dacheng Tao |
| 2026 | Nip Rumors in the Bud: Retrieval-Guided Topic-Level Adaptation for Test-Time Fake News Video Detection. | Jian Lang, Rongpei Hong, Ting Zhong, Yong Wang, Fan Zhou |
| 2026 | From Shallow Humor to Metaphor: Towards Label-Free Harmful Meme Detection via LMM Agent Self-Improvement. | Jian Lang, Rongpei Hong, Ting Zhong, Leiting Chen, Qiang Gao, Fan Zhou |
| 2026 | BSP k-Means. | Sebastian Knzel, Daniel Weiskopf |
| 2026 | MergeRec: Model Merging for Data-Isolated Cross-Domain Sequential Recommendation. | Hyunsoo Kim, Jaewan Moon, Seongmin Park, Jongwuk Lee |
| 2026 | GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning. | Minsu Kim, Seonghyeon Hwang, Steven Euijong Whang |
| 2026 | ARCTraj: A Dataset and Benchmark of Human Reasoning Trajectories for Abstract Problem Solving. | Sejin Kim, Hayan Choi, Seokki Lee, Sundong Kim |
| 2026 | Scaling Recommender Transformers to One Billion Parameters. | Kirill Khrylchenko, Artem Matveev, Sergei S. Makeev, Vladimir Baikalov |
| 2026 | ABLE: Using Adversarial Pairs to Construct Local Models for Explaining Model Predictions. | Krishna Khadka, Sunny Shree, Pujan Budhathoki, Yu Lei, Raghu Kacker, D. Richard Kuhn |
| 2026 | Adversarial Signed Graph Learning with Differential Privacy. | Haobin Ke, Sen Zhang, Qingqing Ye, Xun Ran, Haibo Hu |
| 2026 | SynSym: A Synthetic Data Generation Framework for Psychiatric Symptom Identification. | Migyeong Kang, Jihyun Kim, Hyolim Jeon, Sunwoo Hwang, Jihyun An, Yonghoon Kim, Haewoon Kwak, Jisun An, Jinyoung Han |
| 2026 | AHA: Scalable Alternative History Analysis for Operational Timeseries Applications. | Harshavardhan Kamarthi, Harshil Shah, Henry Milner, Sayan Sinha, Yan Li, B. Aditya Prakash, Vyas Sekar |
| 2026 | Self-Enhanced Density Clustering for High Dimension and Low Sample Size Data. | Bingbing Jiang, Zhongli Wang, Jie Yang, Guangkui Xu, Wei Chen, Chenglong Zhang, Xinyan Liang, Peng Zhou, Weiguo Sheng, Weiping Ding |
| 2026 | MixTTE: Multi-Level Mixture-of-Experts for Scalable and Adaptive Travel Time Estimation. | Wenzhao Jiang, Jindong Han, Ruiqian Han, Hao Liu |
| 2026 | CAVIAR: Disentangling Root Causes with an ICA-based VAE for Large-Scale Microservice Systems. | Xinrui Jiang, Tingzhu Bi, Meng Ma, Ping Wang |
| 2026 | Accelerating Storage-based Training for Graph Neural Networks. | Myung-Hwan Jang, Jeong-Min Park, Yunyong Ko, Sang-Wook Kim |
| 2026 | How to Train Your Mamba for Time Series Forecasting. | Jiaxi Hu, Disen Lan, Ziyu Zhou, Gefeng Luo, Qingsong Wen, Yuxuan Liang |
| 2026 | Uncertainty-Aware Planning for Disambiguating User Intent in Interactive LLM Agents: Application to Baidu Maps. | Deqiang Huang, Xinjiang Lu, Jingbo Zhou, Nijia Lu, Fuxin Li, Bo Hong, Chuanming Zhang, Tong Xu, Enhong Chen |