Ivan Evtimov

According to our database, Ivan Evtimov authored at least 24 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Persistent Pre-Training Poisoning of LLMs.

Yiming Zhang, Javier Rando, Ivan Evtimov, Jianfeng Chi, Eric Michael Smith, Nicholas Carlini, Florian Tramèr, Daphne Ippolito

CoRR, 2024

Gradient-based Jailbreak Images for Multimodal Fusion Models.

Javier Rando, Hannah Korevaar, Erik Brinkman, Ivan Evtimov, Florian Tramèr

CoRR, 2024

Automated Red Teaming with GOAT: the Generative Offensive Agent Tester.

Maya Pavlova, Erik Brinkman, Krithika Iyer, Vitor Albiero, Joanna Bitton, Hailey Nguyen, Joe Li, Cristian Canton-Ferrer, Ivan Evtimov, Aaron Grattafiori

CoRR, 2024

The Llama 3 Herd of Models.

Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurélien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Rozière, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Graeme Nail, Grégoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel M. Kloumann, Ishan Misra, Ivan Evtimov, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, et al.

CoRR, 2024

Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations.

Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, Mark Ibrahim

CoRR, 2024

Towards Red Teaming in Multimodal and Multilingual Translation.

Christophe Ropers, David Dale, Prangthip Hansanti, Gabriel Mejia Gonzalez, Ivan Evtimov, Corinne Wong, Christophe Touret, Kristina Pereyra, Seohyun Sonia Kim, Cristian Canton-Ferrer, Pierre Andrews, Marta R. Costa-jussà

CoRR, 2024

2023

Seamless: Multilingual Expressive and Streaming Speech Translation.

Loïc Barrault, Yu-An Chung, Mariano Coria Meglioli, David Dale, Ning Dong, Mark Duppenthaler, Paul-Ambroise Duquenne, Brian Ellis, Hady Elsahar, Justin Haaheim, John Hoffman, Min-Jae Hwang, Hirofumi Inaguma, Christopher Klaiber, Ilia Kulikov, Pengwei Li, Daniel Licht, Jean Maillard, Ruslan Mavlyutov, Alice Rakotoarison, Kaushik Ram Sadagopan, Abinesh Ramakrishnan, Tuan Tran, Guillaume Wenzek, Yilin Yang, Ethan Ye, Ivan Evtimov, Pierre Fernandez, Cynthia Gao, Prangthip Hansanti, Elahe Kalbassi, Amanda Kallet, Artyom Kozhevnikov, Gabriel Mejia Gonzalez, Robin San Roman, Christophe Touret, Corinne Wong, Carleigh Wood, Bokai Yu, Pierre Andrews, Can Balioglu, Peng-Jen Chen, Marta R. Costa-jussà, Maha Elbayad, Hongyu Gong, Francisco Guzmán, Kevin Heffernan, Somya Jain, Justine Kao, Ann Lee, Xutai Ma, Alexandre Mourachko, Benjamin N. Peloquin, Juan Pino, Sravya Popuri, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, Anna Y. Sun, Paden Tomasello, Changhan Wang, Jeff Wang, Skyler Wang, Mary Williamson

CoRR, 2023

Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models.

Manish Bhatt, Sahana Chennabasappa, Cyrus Nikolaidis, Shengye Wan, Ivan Evtimov, Dominik Gabi, Daniel Song, Faizan Ahmad, Cornelius Aschermann, Lorenzo Fontana, Sasha Frolov, Ravi Prakash Giri, Dhaval Kapil, Yiannis Kozyrakis, David LeBlanc, James Milazzo, Aleksandar Straumann, Gabriel Synnaeve, Varun Vontimitta, Spencer Whitman, Joshua Saxe

CoRR, 2023

Code Llama: Open Foundation Models for Code.

Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton-Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, Gabriel Synnaeve

CoRR, 2023

VPA: Fully Test-Time Visual Prompt Adaptation.

Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas

Proceedings of the 31st ACM International Conference on Multimedia, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Confusing Large Models by Confusing Small Models.

Vítor Albiero, Raghav Mehta, Ivan Evtimov, Samuel J. Bell, Levent Sagun, Aram Markosyan

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others.

Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

You Only Need a Good Embeddings Extractor to Fix Spurious Correlations.

Raghav Mehta, Vítor Albiero, Li Chen, Ivan Evtimov, Tamar Glaser, Zhiheng Li, Tal Hassner

CoRR, 2022

Adversarial Text Normalization.

Joanna Bitton, Maya Pavlova, Ivan Evtimov

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 2022

2021

Disrupting Machine Learning: Emerging Threats and Applications for Privacy and Dataset Ownership.

Ivan Evtimov

PhD thesis, 2021

FoggySight: A Scheme for Facial Lookup Privacy.

Ivan Evtimov, Pascal Sturmfels, Tadayoshi Kohno

Proc. Priv. Enhancing Technol., 2021

Disrupting Model Training with Adversarial Shortcuts.

Ivan Evtimov, Ian Covert, Aditya Kusupati, Tadayoshi Kohno

CoRR, 2021

2020

Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption.

Ivan Evtimov, Russ Howes, Brian Dolhansky, Hamed Firooz, Cristian Canton-Ferrer

CoRR, 2020

Security and Machine Learning in the Real World.

Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno, Jerry Li

CoRR, 2020

2018

Physical Adversarial Examples for Object Detectors.

Dawn Song, Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Florian Tramèr, Atul Prakash, Tadayoshi Kohno

Proceedings of the 12th USENIX Workshop on Offensive Technologies, 2018

Robust Physical-World Attacks on Deep Learning Visual Classification.

Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, Dawn Song

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Note on Attacking Object Detectors with Adversarial Stickers.

Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Dawn Song, Tadayoshi Kohno, Amir Rahmati, Atul Prakash, Florian Tramèr

CoRR, 2017

Robust Physical-World Attacks on Machine Learning Models.

Ivan Evtimov, Kevin Eykholt, Earlence Fernandes, Tadayoshi Kohno, Bo Li, Atul Prakash, Amir Rahmati, Dawn Song

CoRR, 2017