| 2026 | Group Fair Matchings Using Convex Cost Functions. | Atasi Panda, Harsh Sharma, Anand Louis, Prajakta Nimbhorkar |
| 2026 | Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks. | Muthukumar Pandaram, Jakob J. Hollenstein, David Drexel, Samuele Tosatto, Antonio Jose Rodrguez-Snchez, Justus H. Piater |
| 2026 | Prototype Entropy Alignment: Reinforcing Structured Uncertainty in LLM Reasoning. | Zhengyuan Pan, Yanhao Chen, Zhongquan Jian, Wanru Zhao, Haonan Ma, Meihong Wang, Qingqiang Wu |
| 2026 | LORETTA: A Low Resource Framework to Poison Continuous Time Dynamic Graphs. | Himanshu Pal, Venkata Sai Pranav Bachina, Ankit Gangwal, Charu Sharma |
| 2026 | Driving Engagement in Daily Fantasy Sports with a Scalable and Urgency-Aware Ranking Engine. | Unmesh Padalkar |
| 2026 | Policy Newton Methods for Distortion Riskmetrics. | Soumen Pachal, Mizhaan Prajit Maniyar, Prashanth L. A. |
| 2026 | Model Change for Description Logic Concepts. | Ana Ozaki, Jandson S. Ribeiro |
| 2026 | Targeting Borderline Fraudsters: Multi-View Hypergraph Fraud Detection with LLM-Guided Contrastive Learning. | Rui Ou, Kun Zhu, Nana Zhang, Jiangtong Li, Chaochao Chen, Yuhua Xu, Changjun Jiang |
| 2026 | SERL: Self-Examining Reinforcement Learning on Open-Domain. | Weixuan Ou, Yanzhao Zheng, Shuoshuo Sun, Wei Zhang, Baohua Dong, Hangcheng Zhu, Ruohui Huang, Gang Yu, Pengwei Yan, Yifan Qiao |
| 2026 | Taming the Phantom: Token-Asymmetric Filtering for Hallucination Mitigation in Large Vision-Language Models. | Shuyi Ouyang, Hongyi Wang, Gongfan Fang, Xinyin Ma, Lanfen Lin, Xinchao Wang |
| 2026 | PMPGuard: Catching Pseudo-Matched Pairs in Remote Sensing Image-Text Retrieval. | Pengxiang Ouyang, Qing Ma, Zheng Wang, Cong Bai |
| 2026 | Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN. | Kaichen Ouyang, Zong Ke, Shengwei Fu, Lingjie Liu, Puning Zhao, Dayu Hu |
| 2026 | DSCodeBench: A Realistic Benchmark for Data Science Code Generation. | Shuyin Ouyang, Dong Huang, Jingwen Guo, Zeyu Sun, Qihao Zhu, Jie M. Zhang |
| 2026 | SpikingIR: A Novel Converted Spiking Neural Network for Efficient Image Restoration. | Yang Ouyang, Zihan Cheng, Xiaotong Luo, Guoqi Li, Yanyun Qu |
| 2026 | DisCo DETR: Distance-aware Multi-view Contrastive Learning for DETR Pre-training. | Chao Ouyang, Yuyang Bai, Jun Zhang, Tianlu Gao, Jun Hao, Lijun Kong, David Wenzhong Gao |
| 2026 | DeLightMono: Enhancing Self-Supervised Monocular Depth Estimation in Endoscopy by Decoupling Uneven Illumination. | Mingyang Ou, Haojin Li, Yifeng Zhang, Ke Niu, Zhongxi Qiu, Heng Li, Jiang Liu |
| 2026 | ParaDySe: A Parallel Strategy Switching Framework for Dynamic Sequences in Transformer-based Large Language Models. | Zhixin Ou, Peng Liang, Linbo Qiao, Jianchen Han, Baihui Liu |
| 2026 | GateRA: Token-aware Modulation for Parameter-Efficient Fine-tuning. | Jie Ou, Shuaihong Jiang, Yingjun Du, Cees G. M. Snoek |
| 2026 | Learning in Zero-Sum Markov Games: Relaxing Strong Reachability and Mixing Time Assumptions. | Reda Ouhamma, Maryam Kamgarpour |
| 2026 | GSAP-ERE: Fine-Grained Scholarly Entity and Relation Extraction Focused on Machine Learning. | Wolfgang Otto, Lu Gan, Sharmila Upadhyaya, Saurav Karmakar, Stefan Dietze |
| 2026 | The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms. | Hikari Otsuka, Daiki Chijiwa, Yasuyuki Okoshi, Daichi Fujiki, Susumu Takeuchi, Masato Motomura |
| 2026 | Behavioral-Similarity and Clustering-Based Methods for Static Graph Estimation in Hybrid GNNs (Student Abstract). | Ryusei Otani, Keiichi Namikoshi, Yuko Sakurai, Mingyu Guo, Satoshi Oyama |
| 2026 | LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding. | Julian Ost, Andrea Ramazzina, Amogh Joshi, Maximilian Bmer, Mario Bijelic, Felix Heide |
| 2026 | Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework. | Diego Ortego, Marlon Rodrguez, Mario Almagro, Kunal Dahiya, David Jimnez, Juan C. SanMiguel |
| 2026 | Computing Probabilistic Explanations for ML Models: Fixed-Parameter Algorithms. | Sebastian Ordyniak, Mateusz Rychlicki, Stefan Szeider |