[ICLR 2026] Ruimeng Ye, Zihan Wang, Zinan Ling, Yang Xiao, Manling Li, Xiaolong Ma, Bo Hui, “Your Language Model Secretly Contains Personality Subnetworks”, in the Fourteenth International Conference on Learning Representations.

[ICLR 2026] Ruimeng Ye, Zihan Wang, Yang Xiao, Zinan Ling, Manling Li, Bo Hui, “Weak-to-Strong Generalization with Failure Trajectories”, in the Fourteenth International Conference on Learning Representations.

[ICLR 2026] Kaiyuan Deng, Gen Li, Yang Xiao, Bo Hui, Xiaolong Ma, “Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models”, in the Fourteenth International Conference on Learning Representations.

[ICML 2026] Xian Gao, Bo Hui , Min-Te Sun, Wei-Shinn Ku, “On the Fragility of Data Attribution When Learning Is Distributed”, in the Forty-third International Conference on Machine Learning.

[ICML 2026] Kaiyuan Deng, Bo Hui, Gen Li, Jie Ji, Minghai Qin, Geng Yuan, Xiaolong Ma, “Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking”, in the Forty-third International Conference on Machine Learning.

[ICCV 2025] Yang Xiao, Wang Lu, Jie Ji, Ruimeng Ye, Gen Li, Xiaolong Ma, Bo Hui, “Optimal Transport for Brain-Image Alignment: Unveiling Redundancy and Synergy in Neural Information Processing”, in Proceedings of the International Conference on Computer Vision.

[ICCV 2025] Gen Li, Yang Xiao, Jie Ji, Kaiyuan Deng, Bo Hui, Linke Guo, Xiaolong Ma, “Sculpting Memory: Multi-Concept Forgetting in Diffusion Models via Dynamic Mask and Concept-Aware Optimization”, in Proceedings of the International Conference on Computer Vision.

[CIKM 2025] Yang Xiao, Ruimeng Ye, Bohan Liu, Xiaolong Ma, Bo Hui, “Efficient Knowledge Graph Unlearning with Zeroth-order Information,” in the 34th ACM International Conference on Information and Knowledge Management.

[COLING 2025] Yang Xiao, Ruimeng Ye, Bo Hui, “Knowledge Graph Unlearning with Schema,” in the 31st International Conference on Computational Linguistics

[ECAI 2025] Bohan Liu, Yang Xiao, Ruimeng Ye, Zinan Ling, Xiaolong Ma, Bo Hui, "Towards Distributed Backdoor Attacks with Network Detection in Decentralized Federated Learning” in the 28th European Conference on Artificial Intelligence.

[KDD 2025] Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng, “Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective,” in 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

[ICLR 2025] Ruimeng Ye, Yang Xiao, Bo Hui, “Weak-to-Strong Generalization beyond Accuracy: a Pilot Study in Safety, Toxicity, and Legal Reasoning,” in the Thirteenth International Conference on Learning Representations (ICLR) Workshop on Bidirectional Human-AI Alignment.

[NeurIPS 2025] Zinan Ling, Yi Shi, Brett A. McKinney, Da Yan, Yang Zhou, Bo Hui, “Demystify Protein Generation with Hierarchical Conditional Diffusion Models,” in the Reach and Limits of AI for Scientific Discovery at NeurIPS 2025.

[NeurIPS 2025] Yang Xiao, Gen Li, Jie Ji, Ruimeng Ye, Xiaolong Ma, Bo Hui, “The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models,” in the 3rd Workshop on Regulatable ML at NeurIPS 2025.

[GECCO 2025] Po-wei Harn, Bo Hui, Libo Sun, Wei-Shinn Ku, “Evolutionary Quadtree Pooling for Convolutional Neural Networks,” in 2025 International Joint Conference on Neural Networks.

[IJCNN 2025] Ali Murad, Bo Hui, Wei-Shinn Ku, “Optimized Local Updates in Federated Learning via Reinforcement Learning,” in 2025 International Joint Conference on Neural Networks.

[CIKM 2024] Yang Xiao, Zijie Zhang, Yuchen Fang, Da Yan, Yang Zhou, Wei-Shinn Ku, Bo Hui, “Advancing Certified Robustness of Explanation via Gradient Quantization,” in 33rd ACM International Conference on Information and Knowledge Management.

[24’LoG] Yang Xiao, Ruimeng Ye, Bo Hui, “Knowledge Graph Unlearning with Schema (Extended Abstract),” in the Third Learning on Graphs Conference (LoG, 2024).

[24’ICIP] Ziang Shi, Yang Xiao, Da Yan, Min-Te Sun, Wei-Shinn Ku, Bo Hui, “BMT-BENCH: A benchmark sports dataset for video generation,” in the 2024 IEEE International Conference on Image Processing (ICIP, 2024).

[24’ICMLC] Song Gao, Bo Hui, Wanwan Li “Image Generation of Egyptian Hieroglyphs,” in the 2024 16th International Conference on Machine Learning and Computing (ICMLC, 2024).

[23’ICLR] Bo Hui, Da Yan, Xiaolong Ma, and Wei-Shinn Ku, “Rethinking Graph Lottery Tickets: Graph Sparsity Matters,” in the 11th International Conference on Learning Representations (ICLR, 2023).

[23’AAAI] Bo Hui, Yuchen Fang, Tian Xia, Sarp Aykent, and Wei-Shinn Ku, “Constrained Market Share Maximization by Signal-guided Optimization,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI, 2023).

[23’GECCO] Po-wei Harn, Bo Hui, Sai Deepthi Yeddula, Libo Sun, Min-Te Sun, and Wei-Shinn Ku, “A Novel Quadtree-Based Genetic Programming Search for Searchable Encryption Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Lisboa, Portugal, 2023.

[23’SIGSPATIAL] Sai Deepthi Yeddula, Chen Jiang, Bo Hui and Wei-Shinn Ku, “Traffic Accident Hotspot Prediction Using Temporal Convolutional Networks: A Spatio-Temporal Approach”, in 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL, 2023).

[23’Neurips] Chao Jiang, Bo Hui, Bohan Liu, Da Ya, “Successfully Applying Lottery Ticket Hypothesis to Diffusion Model”, in 37th Conference on Neural Information Processing Systems workshop on diffusion models (Neurips 2023).

[22’KDD] Bo Hui and Wei-Shinn Ku, “Low-rank Nonnegative Tensor Decomposition in Hyperbolic Space,” in Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD, 2022).

[22’ICDE] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “Time-sensitive POI Recommendation by Tensor Completion with Side Information,” in Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE, 2022).

[22’EMNLP] Bo Hui, Tian Xia, and Wei-Shinn Ku, “A Localized Geometric Method to Match Knowledge in Low-dimensional Hyperbolic Space,” in Conference on Empirical Methods in Natural Language Processing (EMNLP, 2022).

[22’BigData] Tian Xia, Bo Hui, and Wei-Shinn Ku, “APIP: Attention-based Protein Representation Learning for Protein-Ligand Interface Prediction,” in Proceedings of the IEEE International Conference on Big Data (BigData, 2022).

[22’BigData] Po-Wei Harn, Sai Deepthi Yeddula, Bo Hui, Jie Zhang, Libo Sun, Min-Te Sun, and Wei-Shinn Ku, “IGRP: Iterative Gradient Rank Pruning for Finding Graph Lottery Ticket,” in Proceedings of the IEEE International Conference on Big Data (BigData, 2022).

[21’BigData] Bo Hui, Da Yan, and Wei-Shinn Ku, “Node-Polysemy Aware Recommendation by Matrix Completion with Side Information,” in Proceedings of the IEEE International Conference on Big Data (BigData, 2021).

[21’MSN] Bo Hui, Chen Jiang, Pavani Ankireddy, Wenlu Wang, and Wei-Shinn Ku, “Indoor Navigation for Users with Mobility Aids Using Smartphones and Neighborhood Networks,” In Proceedings of The 17th International Conference on Mobility, Sensing and Networking (MSN, 2021).

[21’KDD] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction,” in Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD, 2021).

[21’ICDE] Bo Hui, Haiquan Chen, Da Yan, and Wei-Shinn Ku, “EDGE: Entity-Diffusion Gaussian Ensemble for Interpretable Tweet Geolocation Prediction,” in Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE, 2021).

[21’ICDM] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “Trajectory WaveNet: A Trajectory-Based Model for Traffic Forecasting,” in Proceedings of the 21st IEEE International Conference on Data Mining (ICDM, 2021).

[20’CIKM] Bo Hui, Da Yan, Wei-Shinn Ku, and Wenlu Wang, “Predicting Economic Growth by Region Embedding: A Multigraph Convolutional Network Approach,” in Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM, 2020).

[IEEE Transactions on Intelligent Vehicles] Yuchen Fang, Yanjun Qin, Haiyong Luo, Fang Zhao, Liang Zeng, Bo Hui, Chenxing Wang, “CDGNet: A Cross-Time Dynamic Graph-Based Deep Learning Model for Vehicle-Based Traffic Speed Forecasting."