By Associate Professor Piotr Koniusz

Conference Papers

Zhang Y; Zhu H; Shi H; Chen Y; Han X; Zhang Y; Song L; Wang W; Zhou C; Shang X; Koniusz P, 2026, 'FLASH: Fast Generative Retrieval via Autoregressive Semantic Hashing with Provably Distance Bounds', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 6594 - 6605, http://dx.doi.org/10.1145/3770855.3817800

Zhang Y; Zhu H; Shi H; Dong J; Song L; Han X; Chen Y; Wang W; Yu H; Shang X; Koniusz P, 2026, 'When Gradient Boosting Meets Adapter: Exploring Weak Learners for Parameter-Efficient Fine-tuning of LLMs', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 6606 - 6617, http://dx.doi.org/10.1145/3770855.3817971

Ding X; Wang L; Koniusz P; Gao Y, 2026, 'Learning Time in Static Classifiers', in Proceedings of the Aaai Conference on Artificial Intelligence, pp. 20816 - 20825, http://dx.doi.org/10.1609/aaai.v40i25.39221

Dong J; Koniusz P; Qu X; Ong YS, 2025, 'Stabilizing Modality Gap & Lowering Gradient Norms Improve Zero-Shot Adversarial Robustness of VLMs', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 236 - 247, http://dx.doi.org/10.1145/3690624.3709296

Zhang Y; Zhu H; Yang M; Liu J; Ying R; King I; Koniusz P, 2025, 'Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1984 - 1995, http://dx.doi.org/10.1145/3690624.3709249

Wijesinghe A; Zhu H; Koniusz P, 2025, 'Graph Self-Supervised Learning with Learnable Structural and Positional Encodings', in Www 2025 Proceedings of the ACM Web Conference, pp. 4053 - 4067, http://dx.doi.org/10.1145/3696410.3714745

Li Y; Moghadam P; Peng C; Ye N; Koniusz P, 2025, 'Inductive Graph Few-shot Class Incremental Learning', in Wsdm 2025 Proceedings of the 18th ACM International Conference on Web Search and Data Mining, pp. 466 - 474, http://dx.doi.org/10.1145/3701551.3703578

Wang L; Koniusz P; Gedeon T; Zheng L, 2025, 'Adaptive Multi-head Contrastive Learning', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 404 - 421, http://dx.doi.org/10.1007/978-3-031-72890-7_25

Dong J; Koniusz P; Chen J; Ong YS, 2025, 'Adversarially Robust Distillation by Reducing the Student-Teacher Variance Gap', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 92 - 111, http://dx.doi.org/10.1007/978-3-031-73235-5_6

Steinberg DM; Wijesinghe A; Oliveira R; Koniusz P; Ong CS; Bonilla EV, 2025, 'Amortized Active Generation of Pareto Sets', in Advances in Neural Information Processing Systems, pp. 95495 - 95520

Zhu H; Zhang Y; Dong J; Koniusz P, 2025, 'BiLoRA: Almost-orthogonal Parameter Spaces for Continual Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 25613 - 25622, http://dx.doi.org/10.1109/CVPR52734.2025.02385

Zhang Y; Zhu H; Dong J; Shi H; Meng Z; Koniusz P; Yu H, 2025, 'CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning', in Advances in Neural Information Processing Systems, pp. 156796 - 156818

Ding X; Wang L; Koniusz P; Gao Y, 2025, 'Graph Your Own Prompt', in Advances in Neural Information Processing Systems, pp. 42542 - 42587

Dong J; Koniusz P; Zhang Y; Zhu H; Liu W; Qu X; Ong YS, 2025, 'Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices', in Proceedings of Machine Learning Research, pp. 14061 - 14078

Ding D; Wang L; Zhu L; Gedeon T; Koniusz P, 2025, 'LEARNABLE EXPANSION OF GRAPH OPERATORS FOR MULTI-MODAL FEATURE FUSION', in 13th International Conference on Learning Representations Iclr 2025, pp. 78379 - 78401

Dong J; Zhu H; Zhang Y; Qu X; Ong YS; Koniusz P, 2025, 'Machine Unlearning viaTask Simplex Arithmetic', in Advances in Neural Information Processing Systems, pp. 184768 - 184799

Ni Y; Wen S; Koniusz P; Cherian A, 2025, 'Noise Consistency Regularization for Improved Subject-Driven Image Synthesis', in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 3107 - 3117, http://dx.doi.org/10.1109/CVPRW67362.2025.00294

Zhang S; Ni Y; Du J; Xue Y; Torr P; Koniusz P; Den Hengel AV, 2025, 'Open-World Objectness Modeling Unifies Novel Object Detection', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 30332 - 30342, http://dx.doi.org/10.1109/CVPR52734.2025.02824

Lu C; Liu Z; Koniusz P, 2025, 'OpenKD: Opening Prompt Diversity for Zero- and Few-Shot Keypoint Detection', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 148 - 165, http://dx.doi.org/10.1007/978-3-031-72655-2_9

Zhang S; Chen A; Sun Y; Gu J; Zheng YY; Koniusz P; Zou K; van den Hengel A; Xue Y, 2025, 'Primitive Vision: Improving Diagram Understanding in MLLMs', in Proceedings of Machine Learning Research, pp. 74732 - 74755

Zhu H; Steinberg DM; Koniusz P, 2025, 'Protein Fitness Landscape: Spectral Graph Theory Perspective', in Proceedings of Machine Learning Research, pp. 2827 - 2835

Dong J; Zhang C; Qu X; Ma Z; Koniusz P; Ong YS, 2025, 'Robust SuperAlignment: Weak-to-Strong Robustness Generalization for Vision-Language Models', in Advances in Neural Information Processing Systems, pp. 20822 - 20854

Dong J; Koniusz P; Feng L; Zhang Y; Zhu H; Liu W; Qu X; Ong YS, 2025, 'Robustifying Zero-Shot Vision Language Models by Subspaces Alignment', in Proceedings of the IEEE International Conference on Computer Vision, pp. 21037 - 21047, http://dx.doi.org/10.1109/ICCV51701.2025.01955

Zhang Y; Zhu H; Song Z; Chen Y; Fu X; Meng Z; Koniusz P; King I, 2024, 'Geometric View of Soft Decorrelation in Self-Supervised Learning', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 4338 - 4349, http://dx.doi.org/10.1145/3637528.3671914

Lu C; Koniusz P, 2024, 'Detect Any Keypoints: An Efficient Light-Weight Few-Shot Keypoint Detector', in Proceedings of the Aaai Conference on Artificial Intelligence, pp. 3882 - 3890, http://dx.doi.org/10.1609/aaai.v38i4.28180

Shi W; Lu C; Shao M; Zhang Y; Xia S; Koniusz P, 2024, 'Few-shot Shape Recognition by Learning Deep Shape-aware Features', in Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Wacv 2024, pp. 1837 - 1848, http://dx.doi.org/10.1109/WACV57701.2024.00186

Zhang S; Ni Y; Du J; Liu Y; Koniusz P, 2024, 'Semantic Transfer from Head to Tail: Enlarging Tail Margin for Long-Tailed Visual Recognition', in Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Wacv 2024, pp. 1339 - 1349, http://dx.doi.org/10.1109/WACV57701.2024.00138

Dong J; Koniusz P; Chen J; Xie X; Ong YS, 2024, 'Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 28535 - 28544, http://dx.doi.org/10.1109/CVPR52733.2024.02696

Ni Y; Koniusz P, 2024, 'CHAIN: Enhancing Generalization in Data-Efficient GANs via LipsCHitz Continuity ConstrAIned Normalization', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 6763 - 6774, http://dx.doi.org/10.1109/CVPR52733.2024.00646

Wang L; Koniusz P, 2024, 'FLOW DYNAMICS CORRECTION FOR ACTION RECOGNITION', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, pp. 3795 - 3799, http://dx.doi.org/10.1109/ICASSP48485.2024.10446223

Wang L; Sun K; Koniusz P, 2024, 'HIGH-ORDER TENSOR POOLING WITH ATTENTION FOR ACTION RECOGNITION', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, pp. 3885 - 3889, http://dx.doi.org/10.1109/ICASSP48485.2024.10446900

Chen Q; Wang L; Koniusz P; Gedeon T, 2024, 'Motion meets Attention: Video Motion Prompts', in Proceedings of Machine Learning Research, pp. 591 - 606

Ni Y; Zhang S; Koniusz P, 2024, 'PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization', in Advances in Neural Information Processing Systems

Haghighat M; Moghadam P; Mohamed S; Koniusz P, 2024, 'PRE-TRAINING WITH RANDOM ORTHOGONAL PROJECTION IMAGE MODELING', in 12th International Conference on Learning Representations Iclr 2024

Dong J; Koniusz P; Chen J; Wang ZJ; Ong YS, 2024, 'Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 28432 - 28442, http://dx.doi.org/10.1109/CVPR52733.2024.02686

Zhang Y; Zhu H; Song Z; Koniusz P; King I, 2023, 'Spectral Feature Augmentation for Graph Contrastive Learning and Beyond', in Proceedings of the 37th Aaai Conference on Artificial Intelligence Aaai 2023, pp. 11289 - 11297, http://dx.doi.org/10.1609/aaai.v37i9.26336

Prabowo A; Shao W; Xue H; Koniusz P; Salim FD, 2023, 'Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting', in ACM International Conference Proceeding Series, pp. 93 - 104, http://dx.doi.org/10.1145/3576842.3582362

Wang L; Koniusz P, 2023, '3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 5620 - 5631, http://dx.doi.org/10.1109/CVPR52729.2023.00544

Kang D; Koniusz P; Cho M; Murray N, 2023, 'Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 19627 - 19638, http://dx.doi.org/10.1109/CVPR52729.2023.01880

Zhang H; Torr PHS; Koniusz P, 2023, 'Improving Few-shot Learning by Spatially-aware Matching and CrossTransformer', in Lecture Notes in Computer Science, pp. 3 - 20, http://dx.doi.org/10.1007/978-3-031-26348-4_1

Rahman S; Koniusz P; Wang L; Zhou L; Moghadam P; Sun C, 2023, 'Learning Partial Correlation based Deep Visual Representation for Image Classification', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 6231 - 6242, http://dx.doi.org/10.1109/CVPR52729.2023.00603

Zhang Z; Wang L; Zhou L; Koniusz P, 2023, 'Learning Spatial-context-aware Global Visual Feature Representation for Instance Image Retrieval', in Proceedings of the IEEE International Conference on Computer Vision, pp. 11216 - 11225, http://dx.doi.org/10.1109/ICCV51070.2023.01033

Zhang Y; Zhu H; Chen Y; Song Z; Koniusz P; King I, 2023, 'Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective', in Advances in Neural Information Processing Systems

Ni Y; Koniusz P, 2023, 'NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs', in Advances in Neural Information Processing Systems

Wang L; Koniusz P, 2023, 'Temporal-Viewpoint Transportation Plan for Skeletal Few-Shot Action Recognition', in Lecture Notes in Computer Science, pp. 307 - 326, http://dx.doi.org/10.1007/978-3-031-26316-3_19

Zhu H; Koniusz P, 2023, 'Transductive Few-Shot Learning with Prototype-Based Label Propagation by Iterative Graph Refinement', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 23996 - 24006, http://dx.doi.org/10.1109/CVPR52729.2023.02298

Zhang Y; Zhu H; Song Z; Koniusz P; King I, 2022, 'COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2524 - 2534, http://dx.doi.org/10.1145/3534678.3539425

Zhang Y; Zhu H; Meng Z; Koniusz P; King I, 2022, 'Graph-adaptive Rectified Linear Unit for Graph Neural Networks', in Www 2022 Proceedings of the ACM Web Conference 2022, pp. 1331 - 1339, http://dx.doi.org/10.1145/3485447.3512159

Zhu H; Koniusz P, 2022, 'EASE: Unsupervised Discriminant Subspace Learning for Transductive Few-Shot Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 9068 - 9078, http://dx.doi.org/10.1109/CVPR52688.2022.00887

Lu C; Koniusz P, 2022, 'Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 19394 - 19404, http://dx.doi.org/10.1109/CVPR52688.2022.01881

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