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2024 Conference Publication Embark on DenseQuest: a system for selecting the best dense retriever for a custom collectionKhramtsova, Ekaterina, Leelanupab, Teerapong, Zhuang, Shengyao, Baktashmotlagh, Mahsa and Zuccon, Guido (2024). Embark on DenseQuest: a system for selecting the best dense retriever for a custom collection. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657674 |
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2024 Conference Publication Leveraging LLMs for unsupervised dense retriever rankingKhramtsova, Ekaterina, Zhuang, Shengyao, Baktashmotlagh, Mahsa and Zuccon, Guido (2024). Leveraging LLMs for unsupervised dense retriever ranking. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657798 |
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2024 Conference Publication Domain-aware knowledge distillation for continual model generalizationReddy, Nikhil, Baktashmotlagh, Mahsa and Arora, Chetan (2024). Domain-aware knowledge distillation for continual model generalization. 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-8 January 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/wacv57701.2024.00075 |
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2023 Conference Publication Selecting which dense retriever to use for zero-shot searchKhramtsova, Ekaterina, Zhuang, Shengyao, Baktashmotlagh, Mahsa, Wang, Xi and Zuccon, Guido (2023). Selecting which dense retriever to use for zero-shot search. SIGIR-AP 2023 - Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, Beijing, China, 26-28 November 2023. New York, United States: Association for Computing Machinery. doi: 10.1145/3624918.3625330 |
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2023 Conference Publication How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their TransferabilityWang, Zijian, Luo, Yadan, Zheng, Liang, Huang, Zi and Baktashmotlagh, Mahsa (2023). How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00511 |
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2023 Conference Publication Domain Generalization Guided by Gradient Signal to Noise Ratio of ParametersMichalkiewicz, Mateusz, Faraki, Masoud, Yu, Xiang, Chandraker, Manmohan and Baktashmotlagh, Mahsa (2023). Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00568 |
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2023 Conference Publication KECOR: Kernel Coding Rate Maximization for Active 3D Object DetectionLuo, Yadan, Chen, Zhuoxiao, Fang, Zhen, Zhang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2021. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.01676 |
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2023 Conference Publication Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-LabelingChen, Zhuoxiao, Luo, Yadan, Wang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00344 |
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2023 Conference Publication Exploring active 3D object detection from a generalization perspectiveLuo, Yadan, Chen, Zhuoxiao, Wang, Zijian, Yu, Xin, Huang, Zi and Baktashmotlagh, Mahsa (2023). Exploring active 3D object detection from a generalization perspective. 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, 1 - 5 May 2023. New York, NY, United States: Cornell Tech. doi: 10.48550/arXiv.2301.09249 |
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2023 Conference Publication Center-aware adversarial augmentation for single domain generalizationChen, Tianle, Baktashmotlagh, Mahsa, Wang, Zijian and Salzmann, Mathieu (2023). Center-aware adversarial augmentation for single domain generalization. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 2-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00414 |
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2023 Conference Publication FFM: injecting out-of-domain knowledge via factorized frequency modificationWang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2023). FFM: injecting out-of-domain knowledge via factorized frequency modification. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00412 |
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2023 Conference Publication Convolutional Persistence as a Remedy to Neural Model AnalysisKhramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2023). Convolutional Persistence as a Remedy to Neural Model Analysis. International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 25-27 April 2023. Brookline, MA United States: ML Research Press. |
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2022 Conference Publication Contrastive Class-aware Adaptation for Domain GeneralizationChen, Tianle, Baktashmotlagh, Mahsa and Salzmann, Mathieu (2022). Contrastive Class-aware Adaptation for Domain Generalization. 2022 26th International Conference on Pattern Recognition (ICPR), Montreal, QC Canada, 21-25 August 2022. Piscataway, NJ United States: IEEE. doi: 10.1109/icpr56361.2022.9956262 |
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2022 Conference Publication Rethinking persistent homology for visual recognitionKhramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2022). Rethinking persistent homology for visual recognition. Topological, Algebraic and Geometric Learning Workshops, Online, 25-22 July 2022. Brookline, MA United States: ML Research Press. |
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2022 Conference Publication Modular construction planning using graph neural network heuristic searchHawkins, Philip, Maire, Frederic, Denman, Simon and Baktashmotlagh, Mahsa (2022). Modular construction planning using graph neural network heuristic search. 34th Australasian Joint Conference on Artificial Intelligence (AI), Electr Network, 2-4 February 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-97546-3_19 |
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2022 Conference Publication Learning to generate the unknowns as a remedy to the open-set domain shiftBaktashmotlagh, Mahsa, Chen, Tianle and Salzmann, Mathieu (2022). Learning to generate the unknowns as a remedy to the open-set domain shift. 22nd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-8 January 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV51458.2022.00379 |
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2022 Conference Publication Master of all: simultaneous generalization of urban-scene segmentation to all adverse weather conditionsReddy, Nikhil, Singhal, Abhinav, Kumar, Abhishek, Baktashmotlagh, Mahsa and Arora, Chetan (2022). Master of all: simultaneous generalization of urban-scene segmentation to all adverse weather conditions. Computer Vision – ECCV 2022, Tel Aviv, Israel, 23-27 October 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-19842-7_4 |
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2021 Conference Publication Conditional Extreme Value Theory for Open Set Video Domain AdaptationChen, Zhuoxiao, Luo, Yadan and Baktashmotlagh, Mahsa (2021). Conditional Extreme Value Theory for Open Set Video Domain Adaptation. MMAsia '21: ACM Multimedia Asia, Gold Coast, QLD Australia, 1 - 3 December 2021. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3469877.3490600 |
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2021 Conference Publication Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant EmbeddingsMoskvyak, Olga, Maire, Frederic, Dayoub, Feras, Armstrong, Asia O. and Baktashmotlagh, Mahsa (2021). Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. 2021 Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, QLD Australia, 29 November 2021 - 1 December 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/dicta52665.2021.9647359 |
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2021 Conference Publication Learning to diversify for single domain generalizationWang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087 |
