Zhang, Yingxue

32 publications

ICLR 2026 A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic Joseph Cotnareanu, Didier Chételat, Yingxue Zhang, Mark Coates

TMLR 2026 Extracting and Following Paths for Robust Relational Reasoning with Large Language Models Ge Zhang, Mohammad Ali Alomrani, Hongjian Gu, Jiaming Zhou, Yaochen Hu, Bin Wang, Qun Liu, Mark Coates, Yingxue Zhang, Jianye Hao

ICLR 2026 OmniEVA: Embodied Versatile Planner via Task-Adaptive 3D-Grounded and Embodiment-Aware Reasoning Yuecheng Liu, DaFeng Chi, Shiguang Wu, Zhanguang Zhang, Yuzheng Zhuang, Bowen Yang, He Zhu, Lingfeng Zhang, Pengwei Xie, David Gamaliel Arcos Bravo, Yingxue Zhang, Jianye Hao, Xingyue Quan

ICLR 2026 One Demo Is All It Takes: Planning Domain Derivation with LLMs from a Single Demonstration Jinbang Huang, Yixin Xiao, Zhanguang Zhang, Mark Coates, Jianye Hao, Yingxue Zhang

ICLR 2026 Uncertainty-Aware Gaussian mAP for Vision-Language Navigation Jianzhe Gao, Rui Liu, Yuxuan Xu, Tongtong Cao, Yingxue Zhang, Zhanguang Zhang, Sida Peng, Yi Yang, Wenguan Wang

NeurIPS 2025 C3PO: Optimized Large Language Model Cascades with Probabilistic Cost Constraints for Reasoning Antonios Valkanas, Soumyasundar Pal, Pavel Rumiantsev, Yingxue Zhang, Mark Coates

NeurIPS 2025 Dynamic Masking and Auxiliary Hash Learning for Enhanced Cross-Modal Retrieval Shuang Zhang, Yue Wu, Lei Shi, Yingxue Zhang, Feifei Kou, Huilong Jin, Pengfei Zhang, Meiyu Liang, Mingying Xu

AISTATS 2025 InnerThoughts: Disentangling Representations and Predictions in Large Language Models Didier Chételat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang, Mark Coates

TMLR 2025 Personalized Negative Reservoir for Incremental Learning in Recommender Systems Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates

ICLRW 2025 Refining Answer Distributions for Improved Large Language Model Reasoning Soumyasundar Pal, Didier Chételat, Yingxue Zhang, Mark Coates

TMLR 2025 Sparse Decomposition of Graph Neural Networks Yaochen Hu, Mai Zeng, Ge Zhang, Pavel Rumiantsev, Liheng Ma, Yingxue Zhang, Mark Coates

IJCAI 2025 The Graph's Apprentice: Teaching an LLM Low-Level Knowledge for Circuit Quality Estimation Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chételat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan

NeurIPS 2024 An End-to-End Graph Attention Network Hashing for Cross-Modal Retrieval Huilong Jin, Yingxue Zhang, Lei Shi, Shuang Zhang, Feifei Kou, Jiapeng Yang, Chuangying Zhu, Jia Luo

ICML 2024 CKGConv: General Graph Convolution with Continuous Kernels Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates

TMLR 2024 DyG2Vec: Efficient Representation Learning for Dynamic Graphs Mohammad Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates

NeurIPS 2024 HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates

AISTATS 2024 Multi-Resolution Time-Series Transformer for Long-Term Forecasting Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates

NeurIPS 2024 SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-Situ Observations for Large-Scale Solar Energy Forecasting Ruohan Li, Yiqun Xie, Xiaowei Jia, Dongdong Wang, Yanhua Li, Yingxue Zhang, Zhihao Wang, Zhili Li

TMLR 2024 Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang

IJCAI 2023 A Survey on User Behavior Modeling in Recommender Systems Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang

ICML 2023 Bidirectional Learning for Offline Model-Based Biological Sequence Design Can Chen, Yingxue Zhang, Xue Liu, Mark Coates

AAAI 2023 Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng

AISTATS 2023 Spectral Augmentations for Graph Contrastive Learning Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates

AAAI 2023 Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates

NeurIPSW 2023 Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang

AISTATS 2021 Detection and Defense of Topological Adversarial Attacks on Graphs Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates

AAAI 2021 Knowledge-Enhanced Top-K Recommendation in Poincaré Ball Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates

ICML 2021 RNN with Particle Flow for Probabilistic Spatio-Temporal Forecasting Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates

ICML 2020 Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates

AAAI 2020 Memory Augmented Graph Neural Networks for Sequential Recommendation Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates

UAI 2020 Non Parametric Graph Learning for Bayesian Graph Neural Networks Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates

AAAI 2019 Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay