Torr, Philip

179 publications

TMLR 2026 The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Guibin Zhang, Hejia Geng, Xiaohang Yu, Zhenfei Yin, Zaibin Zhang, Zelin Tan, Heng Zhou, Zhong-Zhi Li, Xiangyuan Xue, Yijiang Li, Yifan Zhou, Yang Chen, Chen Zhang, Yutao Fan, Zihu Wang, Songtao Huang, Francisco Piedrahita Velez, Yue Liao, Hongru Wang, Mengyue Yang, Heng Ji, Jun Wang, Shuicheng Yan, Philip Torr, Lei Bai

ICCV 2025 AlignGuard: Scalable Safety Alignment for Text-to-Image Generation Runtao Liu, I Chieh Chen, Jindong Gu, Jipeng Zhang, Renjie Pi, Qifeng Chen, Philip Torr, Ashkan Khakzar, Fabio Pizzati

ICLRW 2025 Attacking Multimodal OS Agents with Malicious Image Patches Lukas Aichberger, Alasdair Paren, Philip Torr, Yarin Gal, Adel Bibi

ICLR 2025 Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models Wenxuan Zhang, Philip Torr, Mohamed Elhoseiny, Adel Bibi

NeurIPS 2025 Can Knowledge-Graph-Based Retrieval Augmented Generation Really Retrieve What You Need? Junchi Yu, Yujie Liu, Jindong Gu, Philip Torr, Dongzhan Zhou

WACV 2025 Can Multimodal Large Language Models Truly Perform Multimodal In-Context Learning? Shuo Chen, Zhen Han, Bailan He, Jianzhe Liu, Mark Buckley, Yao Qin, Philip Torr, Volker Tresp, Jindong Gu

NeurIPS 2025 Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention Shuang Wu, Youtian Lin, Feihu Zhang, Yifei Zeng, Yikang Yang, Yajie Bao, Jiachen Qian, Siyu Zhu, Xun Cao, Philip Torr, Yao Yao

ICLR 2025 Do as I Do (Safely): Mitigating Task-Specific Fine-Tuning Risks in Large Language Models Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi

ICLRW 2025 Effortless Efficiency: Low-Cost Pruning of Diffusion Models Yang Zhang, Er Jin, Yanfei Dong, Ashkan Khakzar, Philip Torr, Johannes Stegmaier, Kenji Kawaguchi

CVPR 2025 FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models Haokun Chen, Hang Li, Yao Zhang, Jinhe Bi, Gengyuan Zhang, Yueqi Zhang, Philip Torr, Jindong Gu, Denis Krompass, Volker Tresp

ICML 2025 Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation Junlin Han, Jianyuan Wang, Andrea Vedaldi, Philip Torr, Filippos Kokkinos

ICML 2025 Focus on This, Not That! Steering LLMs with Adaptive Feature Specification Tom A. Lamb, Adam Davies, Alasdair Paren, Philip Torr, Francesco Pinto

ICLRW 2025 Focus on This, Not That! Steering LLMs with Adaptive Feature Specification Tom A. Lamb, Adam Davies, Alasdair Paren, Philip Torr, Francesco Pinto

NeurIPS 2025 Jailbreak-AudioBench: In-Depth Evaluation and Analysis of Jailbreak Threats for Large Audio Language Models Hao Cheng, Erjia Xiao, Jing Shao, Yichi Wang, Le Yang, Chao Shen, Philip Torr, Jindong Gu, Renjing Xu

NeurIPS 2025 Large Language Models Miss the Multi-Agent Mark Emanuele La Malfa, Gabriele La Malfa, Samuele Marro, Jie M. Zhang, Elizabeth Black, Michael Luck, Philip Torr, Michael J. Wooldridge

CVPR 2025 Localizing Events in Videos with Multimodal Queries Gengyuan Zhang, Mang Ling Ada Fok, Jialu Ma, Yan Xia, Daniel Cremers, Philip Torr, Volker Tresp, Jindong Gu

ICLRW 2025 MALT: Improving Reasoning with Multi-Agent LLM Training Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Rafael Rafailov, Ivan Laptev, Philip Torr, Fabio Pizzati, Ronald Clark, Christian Schroeder de Witt

NeurIPS 2025 MIP Against Agent: Malicious Image Patches Hijacking Multimodal OS Agents Lukas Aichberger, Alasdair Paren, Guohao Li, Philip Torr, Yarin Gal, Adel Bibi

ICCV 2025 MatchDiffusion: Training-Free Generation of Match-Cuts Alejandro Pardo, Fabio Pizzati, Tong Zhang, Alexander Pondaven, Philip Torr, Juan Camilo Perez, Bernard Ghanem

NeurIPS 2025 Measuring What Matters: Construct Validity in Large Language Model Benchmarks Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou, Franziska Sofia Hafner, Harry Mayne, Jan Batzner, Negar Foroutan, Chris Schmitz, Karolina Korgul, Hunar Batra, Oishi Deb, Emma Beharry, Cornelius Emde, Thomas Foster, Anna Gausen, María Grandury, Simeng Han, Valentin Hofmann, Lujain Ibrahim, Hazel Kim, Hannah Rose Kirk, Fangru Lin, Gabrielle Kaili-May Liu, Lennart Luettgau, Jabez Magomere, Jonathan Rystrøm, Anna Sotnikova, Yushi Yang, Yilun Zhao, Adel Bibi, Antoine Bosselut, Ronald Clark, Arman Cohan, Jakob Nicolaus Foerster, Yarin Gal, Scott A. Hale, Inioluwa Deborah Raji, Christopher Summerfield, Philip Torr, Cozmin Ududec, Luc Rocher, Adam Mahdi

ICML 2025 Minimalist Concept Erasure in Generative Models Yang Zhang, Er Jin, Yanfei Dong, Yixuan Wu, Philip Torr, Ashkan Khakzar, Johannes Stegmaier, Kenji Kawaguchi

ICML 2025 Mixture of Experts Made Intrinsically Interpretable Xingyi Yang, Constantin Venhoff, Ashkan Khakzar, Christian Schroeder De Witt, Puneet K. Dokania, Adel Bibi, Philip Torr

CVPR 2025 Olympus: A Universal Task Router for Computer Vision Tasks Yuanze Lin, Yunsheng Li, Dongdong Chen, Weijian Xu, Ronald Clark, Philip Torr

NeurIPS 2025 On the Coexistence and Ensembling of Watermarks Aleksandar Petrov, Shruti Agarwal, Philip Torr, Adel Bibi, John Collomosse

ICLRW 2025 On the Coexistence and Ensembling of Watermarks Aleksandar Petrov, Shruti Agarwal, Philip Torr, Adel Bibi, John Collomosse

CVPR 2025 Open-World Objectness Modeling Unifies Novel Object Detection Shan Zhang, Yao Ni, Jinhao Du, Yuan Xue, Philip Torr, Piotr Koniusz, Anton van den Hengel

CVPRW 2025 PVUW 2025 Challenge Report: Advances in Pixel-Level Understanding of Complex Videos in the Wild Henghui Ding, Chang Liu, Nikhila Ravi, Shuting He, Yunchao Wei, Song Bai, Philip Torr

NeurIPS 2025 Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers Wei Pang, Kevin Qinghong Lin, Xiangru Jian, Xi He, Philip Torr

ICML 2025 PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data Tingchen Fu, Mrinank Sharma, Philip Torr, Shay B Cohen, David Krueger, Fazl Barez

TMLR 2025 Reliable and Responsible Foundation Models Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, Rene Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao

ICLRW 2025 Semantic-Level Confidence Calibration of Language Models via Temperature Scaling Tom A. Lamb, Desi R. Ivanova, Philip Torr, Tim G. J. Rudner

ICLR 2025 Shh, Don't Say That! Domain Certification in LLMs Cornelius Emde, Alasdair Paren, Preetham Arvind, Maxime Guillaume Kayser, Tom Rainforth, Thomas Lukasiewicz, Philip Torr, Adel Bibi

ICLRW 2025 Shh, Don't Say That! Domain Certification in LLMs Cornelius Emde, Alasdair Paren, Preetham Arvind, Maxime Kayser, Tom Rainforth, Thomas Lukasiewicz, Bernard Ghanem, Philip Torr, Adel Bibi

ICCV 2025 Stable Virtual Camera: Generative View Synthesis with Diffusion Models Jensen Zhou, Hang Gao, Vikram Voleti, Aaryaman Vasishta, Chun-Han Yao, Mark Boss, Philip Torr, Christian Rupprecht, Varun Jampani

NeurIPS 2025 Too Late to Recall: Explaining the Two-Hop Problem in Multimodal Knowledge Retrieval Constantin Venhoff, Ashkan Khakzar, Sonia Joseph, Philip Torr, Neel Nanda

ICLR 2025 Towards Certification of Uncertainty Calibration Under Adversarial Attacks Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip Torr, Adel Bibi

ICLR 2025 Towards Interpreting Visual Information Processing in Vision-Language Models Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez

NeurIPS 2025 Towards Reliable Identification of Diffusion-Based Image Manipulations Alex Costanzino, Woody Bayliss, Juil Sock, Marc Gorriz Blanch, Danijela Horak, Ivan Laptev, Philip Torr, Fabio Pizzati

ICLRW 2025 Understanding Reasoning in Thinking Language Models via Steering Vectors Constantin Venhoff, Iván Arcuschin, Philip Torr, Arthur Conmy, Neel Nanda

NeurIPS 2025 VIKI‑R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning Li Kang, Xiufeng Song, Heng Zhou, Yiran Qin, Jie Yang, Xiaohong Liu, Philip Torr, Lei Bai, Zhenfei Yin

ICCV 2025 VMem: Consistent Interactive Video Scene Generation with Surfel-Indexed View Memory Runjia Li, Philip Torr, Andrea Vedaldi, Tomas Jakab

CVPR 2025 Video Motion Transfer with Diffusion Transformers Alexander Pondaven, Aliaksandr Siarohin, Sergey Tulyakov, Philip Torr, Fabio Pizzati

NeurIPSW 2024 A Cautionary Tale on the Evaluation of Differentially Private In-Context Learning Anjun Hu, Jiyang Guan, Philip Torr, Francesco Pinto

TMLR 2024 A Survey on Transferability of Adversarial Examples Across Deep Neural Networks Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr

ICLR 2024 An Image Is Worth 1000 Lies: Transferability of Adversarial Images Across Prompts on Vision-Language Models Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr

ICMLW 2024 An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr

ECCV 2024 CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios Qilang Ye, Zitong Yu, Rui Shao, Xinyu Xie, Philip Torr, Xiaochun Cao

CVPR 2024 CLIP as RNN: Segment Countless Visual Concepts Without Training Endeavor Shuyang Sun, Runjia Li, Philip Torr, Xiuye Gu, Siyang Li

NeurIPSW 2024 CRAB: Cross-Platfrom Agent Benchmark for Multi-Modal Embodied Language Model Agents Tianqi Xu, Linyao Chen, Dai-Jie Wu, Yanjun Chen, Zecheng Zhang, Xiang Yao, Zhiqiang Xie, Yongchao Chen, Shilong Liu, Bochen Qian, Philip Torr, Bernard Ghanem, Guohao Li

ICMLW 2024 Can Editing LLMs Inject Harm? Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu

NeurIPSW 2024 Can Editing LLMs Inject Harm? Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu

ICLRW 2024 Can Large Language Model Agents Simulate Human Trust Behaviors? Chengxing Xie, Canyu Chen, Feiran Jia, Ziyu Ye, Kai Shu, Adel Bibi, Ziniu Hu, Philip Torr, Bernard Ghanem, Guohao Li

ICLR 2024 Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem, Philip Torr, Adel Bibi, Mohamed Elhoseiny

TMLR 2024 Corrective Machine Unlearning Shashwat Goel, Ameya Prabhu, Philip Torr, Ponnurangam Kumaraguru, Amartya Sanyal

ECCV 2024 DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu, Tong He, Wanli Ouyang, Philip Torr, Jian Wu

NeurIPS 2024 Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer Shuang Wu, Youtian Lin, Feihu Zhang, Yifei Zeng, Jingxi Xu, Philip Torr, Xun Cao, Yao Yao

ICML 2024 Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras, Adel Bibi, Rudy R Bunel, Krishnamurthy Dj Dvijotham, Philip Torr, M. Pawan Kumar

ICML 2024 Extracting Training Data from Document-Based VQA Models Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari

ICMLW 2024 Extracting Training Data from Document-Based VQA Models Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari

TMLR 2024 Fine-Tuning Can Cripple Your Foundation Model; Preserving Features May Be the Solution Jishnu Mukhoti, Yarin Gal, Philip Torr, Puneet K. Dokania

TMLR 2024 Foundational Challenges in Assuring Alignment and Safety of Large Language Models Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric J Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Sean O hEigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger

CoLLAs 2024 From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim, Bernard Ghanem, Philip Torr, Adel Bibi

ECCV 2024 GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing Jing Wu, Jia-Wang Bian, Xinghui Li, Guangrun Wang, Ian Reid, Philip Torr, Victor Adrian Prisacariu

NeurIPS 2024 Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr, Ashkan Khakzar, Francesco Pinto

ICLR 2024 Illusory Attacks: Information-Theoretic Detectability Matters in Adversarial Attacks Tim Franzmeyer, Stephen Marcus McAleer, Joao F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt

ECCV 2024 Improving Adversarial Transferability via Model Alignment Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, Jindong Gu

ICLR 2024 Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu

ICLR 2024 Influencer Backdoor Attack on Semantic Segmentation Haoheng Lan, Jindong Gu, Philip Torr, Hengshuang Zhao

NeurIPS 2024 Interpreting Learned Feedback Patterns in Large Language Models Luke Marks, Amir Abdullah, Clement Neo, Rauno Arike, David Krueger, Philip Torr, Fazl Barez

ECCV 2024 Latent Guard: A Safety Framework for Text-to-Image Generation Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati

ICMLW 2024 Mimicking User Data: On Mitigating Fine-Tuning Risks in Closed Large Language Models Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi

ICML 2024 Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators Jianhao Yuan, Francesco Pinto, Adam Davies, Philip Torr

ICMLW 2024 Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators Jianhao Yuan, Francesco Pinto, Adam Davies, Philip Torr

NeurIPSW 2024 OASIS: Open Agents Social Interaction Simulations on One Million Agents Ziyi Yang, Zaibin Zhang, Zirui Zheng, Yuxian Jiang, Ziyue Gan, Zhiyu Wang, Zijian Ling, Konisberg, Martz Ma, Bowen Dong, Prateek Gupta, Shuyue Hu, Zhenfei Yin, Guohao Li, Xu Jia, Lijun Wang, Bernard Ghanem, Huchuan Lu, Wanli Ouyang, Yu Qiao, Philip Torr, Jing Shao

ECCV 2024 On Pretraining Data Diversity for Self-Supervised Learning Hasan Abed Al Kader Hammoud, Tuhin Das, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem

ECCVW 2024 PVUW 2024 Challenge on Complex Video Understanding: Methods and Results Henghui Ding, Chang Liu, Yunchao Wei, Nikhila Ravi, Shuting He, Song Bai, Philip Torr, Deshui Miao, Xin Li, Zhenyu He, Yaowei Wang, Ming-Hsuan Yang, Zhensong Xu, Jiangtao Yao, Chengjing Wu, Ting Liu, Luoqi Liu, Xinyu Liu, Jing Zhang, Kexin Zhang, Yuting Yang, Licheng Jiao, Shuyuan Yang, Mingqi Gao, Jingnan Luo, Jinyu Yang, Jungong Han, Feng Zheng, Bin Cao, Yisi Zhang, Xuanxu Lin, Xingjian He, Bo Zhao, Jing Liu, Feiyu Pan, Hao Fang, Xiankai Lu

ECCV 2024 Placing Objects in Context via Inpainting for Out-of-Distribution Segmentation Pau de Jorge Aranda, Riccardo Volpi, Puneet Dokania, Philip Torr, Gregory Rogez

ICLR 2024 Porf: Pose Residual Field for Accurate Neural Surface Reconstruction Jia-Wang Bian, Wenjing Bian, Victor Adrian Prisacariu, Philip Torr

ICML 2024 Position: Near to Mid-Term Risks and Opportunities of Open-Source Generative AI Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder De Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Rottger, Philip Torr, Trevor Darrell, Yong Suk Lee, Jakob Nicolaus Foerster

ICLRW 2024 Pre-Training Concept Frequency Is Predictive of CLIP Zero-Shot Performance Vishaal Udandarao, Ameya Prabhu, Philip Torr, Adel Bibi, Samuel Albanie, Matthias Bethge

ICML 2024 Prompting a Pretrained Transformer Can Be a Universal Approximator Aleksandar Petrov, Philip Torr, Adel Bibi

ICLR 2024 Real-Fake: Effective Training Data Synthesis Through Distribution Matching Jianhao Yuan, Jie Zhang, Shuyang Sun, Philip Torr, Bo Zhao

NeurIPSW 2024 Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu

ICLRW 2024 Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks? Shuo Chen, Zhen Han, Bailan He, Zifeng Ding, Wenqian Yu, Philip Torr, Volker Tresp, Jindong Gu

CVPR 2024 RoDLA: Benchmarking the Robustness of Document Layout Analysis Models Yufan Chen, Jiaming Zhang, Kunyu Peng, Junwei Zheng, Ruiping Liu, Philip Torr, Rainer Stiefelhagen

ECCV 2024 Scene-Conditional 3D Object Stylization and Composition Jinghao Zhou, Tomas Jakab, Philip Torr, Christian Rupprecht

ICLR 2024 Select to Perfect: Imitating Desired Behavior from Large Multi-Agent Data Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, Joao F. Henriques

CVPR 2024 Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation Hang Li, Chengzhi Shen, Philip Torr, Volker Tresp, Jindong Gu

ICLRW 2024 Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation Hang Li, Chengzhi Shen, Philip Torr, Volker Tresp, Jindong Gu

NeurIPSW 2024 Shh, Don't Say That! Domain Certification in LLMs Cornelius Emde, Preetham Arvind, Alasdair Paren, Maxime Kayser, Tom Rainforth, Thomas Lukasiewicz, Philip Torr, Adel Bibi

ICML 2024 Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation Yibo Yang, Xiaojie Li, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Adel Bibi, Philip Torr, Bernard Ghanem

ECCV 2024 VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models Junlin Han, Filippos Kokkinos, Philip Torr

ICMLW 2024 What Makes and Breaks Safety Fine-Tuning? a Mechanistic Study Samyak Jain, Ekdeep Singh Lubana, Kemal Oksuz, Tom Joy, Philip Torr, Amartya Sanyal, Puneet K. Dokania

ICLR 2024 When Do Prompting and Prefix-Tuning Work? a Theory of Capabilities and Limitations Aleksandar Petrov, Philip Torr, Adel Bibi

ECCV 2024 Which Model Generated This Image? a Model-Agnostic Approach for Origin Attribution Fengyuan Liu, Haochen Luo, Yiming Li, Philip Torr, Jindong Gu

ECCV 2024 WildVidFit: Video Virtual Try-on in the Wild via Image-Based Controlled Diffusion Models Zijian He, Peixin Chen, Guangrun Wang, Guanbin Li, Philip Torr, Liang Lin

TMLR 2024 kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies Zhongrui Gui, Shuyang Sun, Runjia Li, Jianhao Yuan, Zhaochong An, Karsten Roth, Ameya Prabhu, Philip Torr

ECCV 2024 uCAP: An Unsupervised Prompting Method for Vision-Language Models A. Tuan Nguyen, Kai Sheng Tai, Bor-Chun Chen, Satya Narayan Shukla, Hanchao Yu, Philip Torr, Tai-Peng Tian, Ser-Nam Lim

NeurIPSW 2023 AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei, Bernd Bischl, Philip Torr, Ashkan Khakzar, Kenji Kawaguchi

NeurIPS 2023 Benchmarking Robustness of Adaptation Methods on Pre-Trained Vision-Language Models Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip Torr, Volker Tresp

TMLR 2023 Catastrophic Overfitting Can Be Induced with Discriminative Non-Robust Features Guillermo Ortiz-Jimenez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Grégory Rogez, Philip Torr

ICMLW 2023 Certified Calibration: Bounding Worst-Case Calibration Under Adversarial Attacks Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip Torr, Adel Bibi

ICML 2023 Certifying Ensembles: A General Certification Theory with S-Lipschitzness Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip Torr, Adel Bibi

ICMLW 2023 Certifying Ensembles: A General Certification Theory with S-Lipschitzness Aleksandar Petrov, Francisco Eiras, Amartya Sanyal, Philip Torr, Adel Bibi

ICML 2023 Graph Inductive Biases in Transformers Without Message Passing Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim

ICLR 2023 How Robust Is Unsupervised Representation Learning to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICMLW 2023 Illusory Attacks: Detectability Matters in Adversarial Attacks on Sequential Decision-Makers Tim Franzmeyer, Stephen Marcus McAleer, Joao F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt

ICLR 2023 Is Synthetic Data from Generative Models Ready for Image Recognition? Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip Torr, Song Bai, Xiaojuan Qi

NeurIPS 2023 Language Model Tokenizers Introduce Unfairness Between Languages Aleksandar Petrov, Emanuele La Malfa, Philip Torr, Adel Bibi

ICMLW 2023 Language Model Tokenizers Introduce Unfairness Between Languages Aleksandar Petrov, Emanuele La Malfa, Philip Torr, Adel Bibi

ICLR 2023 Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip Torr, Dacheng Tao

ICCV 2023 OxfordTVG-HIC: Can Machine Make Humorous Captions from Images? Runjia Li, Shuyang Sun, Mohamed Elhoseiny, Philip Torr

NeurIPS 2023 ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation Shuyang Sun, Weijun Wang, Andrew Howard, Qihang Yu, Philip Torr, Liang-Chieh Chen

NeurIPSW 2023 Remaining-Useful-Life Prediction and Uncertainty Quantification Using LSTM Ensembles for Aircraft Engines Oishi Deb, Emmanouil Benetos, Philip Torr

NeurIPS 2023 Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-Grained Intersection over Union Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip Torr, Devis Tuia, Tinne Tuytelaars, Luc V Gool, Jiaqian Yu, Matthew Blaschko

NeurIPSW 2023 Towards Flexible, Efficient, and Effective Tensor Product Networks Nanxiang Wang, Chen Lin, Michael Bronstein, Philip Torr

NeurIPSW 2023 When Do Prompting and Prefix-Tuning Work? a Theory of Capabilities and Limitations Aleksandar Petrov, Philip Torr, Adel Bibi

ICMLW 2023 Who to Imitate: Imitating Desired Behavior from Diverse Multi-Agent Datasets Tim Franzmeyer, Jakob Nicolaus Foerster, Edith Elkind, Philip Torr, Joao F. Henriques

AISTATS 2022 Amortized Rejection Sampling in Universal Probabilistic Programming Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schroeder De Witt, Robert Zinkov, Philip Torr, Tom Rainforth, Yee Whye Teh, Frank Wood

TMLR 2022 ANCER: Anisotropic Certification via Sample-Wise Volume Maximization Francisco Eiras, Motasem Alfarra, Philip Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi

ICML 2022 Adversarial Masking for Self-Supervised Learning Yuge Shi, N Siddharth, Philip Torr, Adam R Kosiorek

ICML 2022 Communicating via Markov Decision Processes Samuel Sokota, Christian A Schroeder De Witt, Maximilian Igl, Luisa M Zintgraf, Philip Torr, Martin Strohmeier, Zico Kolter, Shimon Whiteson, Jakob Foerster

ICMLW 2022 Estimating the Impact of Coordinated Inauthentic Behavior on Content Recommendations in Social Networks Swapneel S Mehta, Atilim Gunes Baydin, Bogdan State, Richard Bonneau, Jonathan Nagler, Philip Torr

NeurIPS 2022 FedSR: A Simple and Effective Domain Generalization Method for Federated Learning A. Tuan Nguyen, Philip Torr, Ser Nam Lim

ICLR 2022 Gradient Matching for Domain Generalization Yuge Shi, Jeffrey Seely, Philip Torr, Siddharth N, Awni Hannun, Nicolas Usunier, Gabriel Synnaeve

ICMLW 2022 How Robust Are Pre-Trained Models to Distribution Shift? Yuge Shi, Imant Daunhawer, Julia E Vogt, Philip Torr, Amartya Sanyal

ICLR 2022 KL Guided Domain Adaptation A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, Atilim Gunes Baydin

NeurIPS 2022 Learn What Matters: Cross-Domain Imitation Learning with Task-Relevant Embeddings Tim Franzmeyer, Philip Torr, João F. Henriques

ICLR 2022 Learning Multimodal VAEs Through Mutual Supervision Tom Joy, Yuge Shi, Philip Torr, Tom Rainforth, Sebastian M Schmon, Siddharth N

NeurIPS 2022 Make Some Noise: Reliable and Efficient Single-Step Adversarial Training Pau de Jorge Aranda, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip Torr, Gregory Rogez, Puneet Dokania

NeurIPS 2022 Structure-Preserving 3D Garment Modeling with Neural Sewing Machines Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip Torr, Liang Lin

NeurIPS 2022 Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness Francesco Pinto, Harry Yang, Ser Nam Lim, Philip Torr, Puneet Dokania

AISTATS 2021 Mirror Descent View for Neural Network Quantization Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr, Richad Hartley, Puneet Dokania

NeurIPS 2021 A Continuous Mapping for Augmentation Design Keyu Tian, Chen Lin, Ser Nam Lim, Wanli Ouyang, Puneet Dokania, Philip Torr

NeurIPSW 2021 Are Vision Transformers Always More Robust than Convolutional Neural Networks? Francesco Pinto, Philip Torr, Puneet K. Dokania

ICLR 2021 Capturing Label Characteristics in VAEs Tom Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth

ICMLW 2021 Combating Adversaries with Anti-Adversaries Motasem Alfarra, Juan Camilo Perez, Ali Thabet, Adel Bibi, Philip Torr, Bernard Ghanem

NeurIPS 2021 Do Different Tracking Tasks Require Different Appearance Models? Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip Torr, Luca Bertinetto

NeurIPS 2021 FACMAC: Factored Multi-Agent Centralised Policy Gradients Bei Peng, Tabish Rashid, Christian Schroeder de Witt, Pierre-Alexandre Kamienny, Philip Torr, Wendelin Boehmer, Shimon Whiteson

ICLR 2021 How Benign Is Benign Overfitting ? Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip Torr

NeurIPS 2021 Looking Beyond Single Images for Contrastive Semantic Segmentation Learning Feihu Zhang, Philip Torr, Rene Ranftl, Stephan Richter

NeurIPSW 2021 Mix-MaxEnt: Improving Accuracy and Uncertainty Estimates of Deterministic Neural Networks Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip Torr, Puneet K. Dokania

NeurIPS 2021 Overcoming the Convex Barrier for Simplex Inputs Harkirat Singh Behl, M. Pawan Kumar, Philip Torr, Krishnamurthy Dvijotham

ICLR 2021 Progressive Skeletonization: Trimming More Fat from a Network at Initialization Pau de Jorge, Amartya Sanyal, Harkirat Behl, Philip Torr, Grégory Rogez, Puneet K. Dokania

ICLR 2021 Relating by Contrasting: A Data-Efficient Framework for Multimodal Generative Models Yuge Shi, Brooks Paige, Philip Torr, Siddharth N

ICLR 2021 Scaling the Convex Barrier with Active Sets Alessandro De Palma, Harkirat Behl, Rudy R Bunel, Philip Torr, M. Pawan Kumar

NeurIPSW 2021 Shape-Tailored Deep Neural Networks with PDEs Naeemullah Khan, Angira Sharma, Philip Torr, Ganesh Sundaramoorthi

ICLR 2021 Understanding the Effects of Data Parallelism and Sparsity on Neural Network Training Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr, Martin Jaggi

NeurIPS 2021 You Never Cluster Alone Yuming Shen, Ziyi Shen, Menghan Wang, Jie Qin, Philip Torr, Ling Shao

ECCV 2020 Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation Viveka Kulharia, Siddhartha Chandra, Amit Agrawal, Philip Torr, Ambrish Tyagi

NeurIPS 2020 Calibrating Deep Neural Networks Using Focal Loss Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip Torr, Puneet Dokania

NeurIPS 2020 Continual Learning in Low-Rank Orthogonal Subspaces Arslan Chaudhry, Naeemullah Khan, Puneet Dokania, Philip Torr

WACV 2020 Devon: Deformable Volume Network for Learning Optical Flow Yao Lu, Jack Valmadre, Heng Wang, Juho Kannala, Mehrtash Harandi, Philip Torr

ECCV 2020 Domain-Invariant Stereo Matching Networks Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin Wah, Philip Torr

UAI 2020 Lagrangian Decomposition for Neural Network Verification Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy Dvijotham, Pushmeet Kohli, Philip Torr, M. Pawan Kumar

NeurIPS 2020 Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation Bowen Li, Xiaojuan Qi, Philip Torr, Thomas Lukasiewicz

ECCV 2020 Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection Carlo Biffi, Steven McDonagh, Philip Torr, Aleš Leonardis, Sarah Parisot

NeurIPS 2020 STEER : Simple Temporal Regularization for Neural ODE Arnab Ghosh, Harkirat Behl, Emilien Dupont, Philip Torr, Vinay Namboodiri

ICMLW 2020 WordCraft: An Environment for Benchmarking Commonsense Agents Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip Torr, Shimon Whiteson, Tim Rocktäschel

NeurIPS 2019 Controllable Text-to-Image Generation Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip Torr

NeurIPS 2019 Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip Torr, Victor Lee, Kyle Cranmer, Mr. Prabhat, Frank Wood

ICLR 2019 Meta-Learning with Differentiable Closed-Form Solvers Luca Bertinetto, Joao F. Henriques, Philip Torr, Andrea Vedaldi

NeurIPS 2019 Multi-Agent Common Knowledge Reinforcement Learning Christian Schroeder de Witt, Jakob Foerster, Gregory Farquhar, Philip Torr, Wendelin Boehmer, Shimon Whiteson

ICLR 2019 Snip: Single-Shot Network Pruning Based on Connection Sensitivity Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr

NeurIPS 2019 Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models Yuge Shi, Siddharth N, Brooks Paige, Philip Torr

NeurIPS 2018 A Unified View of Piecewise Linear Neural Network Verification Rudy R Bunel, Ilker Turkaslan, Philip Torr, Pushmeet Kohli, Pawan K Mudigonda

ACML 2018 Deep Fully-Connected Part-Based Models for Human Pose Estimation Rodrigo de Bem, Anurag Arnab, Stuart Golodetz, Michael Sapienza, Philip Torr

NeurIPS 2018 With Friends like These, Who Needs Adversaries? Saumya Jetley, Nicholas Lord, Philip Torr

NeurIPS 2017 Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth N, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah Goodman, Pushmeet Kohli, Frank Wood, Philip Torr

NeurIPS 2016 Adaptive Neural Compilation Rudy R Bunel, Alban Desmaison, Pawan K Mudigonda, Pushmeet Kohli, Philip Torr

NeurIPS 2016 Learning Feed-Forward One-Shot Learners Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip Torr, Andrea Vedaldi

ICML 2015 An Embarrassingly Simple Approach to Zero-Shot Learning Bernardino Romera-Paredes, Philip Torr

CVPR 2014 BING: Binarized Normed Gradients for Objectness Estimation at 300fps Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, Philip Torr

NeurIPS 2013 Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation Vibhav Vineet, Carsten Rother, Philip Torr

NeurIPS 2011 Learning Anchor Planes for Classification Ziming Zhang, Lubor Ladicky, Philip Torr, Amir Saffari

NeurIPS 2008 Improved Moves for Truncated Convex Models Philip Torr, M. P. Kumar

NeurIPS 2007 An Analysis of Convex Relaxations for MAP Estimation Pawan Mudigonda, Vladimir Kolmogorov, Philip Torr