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Philip H. S. Torr

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Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

Feb 26, 2024
Pau de Jorge, Riccardo Volpi, Puneet K. Dokania, Philip H. S. Torr, Gregory Rogez

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Prompting a Pretrained Transformer Can Be a Universal Approximator

Feb 22, 2024
Aleksandar Petrov, Philip H. S. Torr, Adel Bibi

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Self-consistent Validation for Machine Learning Electronic Structure

Feb 15, 2024
Gengyuan Hu, Gengchen Wei, Zekun Lou, Philip H. S. Torr, Wanli Ouyang, Han-sen Zhong, Chen Lin

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RanDumb: A Simple Approach that Questions the Efficacy of Continual Representation Learning

Feb 13, 2024
Ameya Prabhu, Shiven Sinha, Ponnurangam Kumaraguru, Philip H. S. Torr, Ozan Sener, Puneet K. Dokania

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Revealing Decurve Flows for Generalized Graph Propagation

Feb 13, 2024
Chen Lin, Liheng Ma, Yiyang Chen, Wanli Ouyang, Michael M. Bronstein, Philip H. S. Torr

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Secret Collusion Among Generative AI Agents

Feb 12, 2024
Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip H. S. Torr, Lewis Hammond, Christian Schroeder de Witt

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From Categories to Classifier: Name-Only Continual Learning by Exploring the Web

Nov 19, 2023
Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim, Bernard Ghanem, Philip H. S. Torr, Adel Bibi

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When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations

Oct 30, 2023
Aleksandar Petrov, Philip H. S. Torr, Adel Bibi

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Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Oct 30, 2023
Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko

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Segment, Select, Correct: A Framework for Weakly-Supervised Referring Segmentation

Oct 23, 2023
Francisco Eiras, Kemal Oksuz, Adel Bibi, Philip H. S. Torr, Puneet K. Dokania

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