Arman Zharmagambetov

According to our database, Arman Zharmagambetov authored at least 37 papers between 2016 and 2026.

Collaborative distances:

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

2026

How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competition.

Mateusz Dziemian, Maxwell Lin, Xiaohan Fu, Micha Nowak, Nick Winter, Eliot Krzysztof Jones, Andy Zou, Lama Ahmad, Kamalika Chaudhuri, Sahana Chennabasappa, Xander Davies, Lauren Deason, Benjamin L. Edelman, Tanner Emek, Ivan Evtimov, Jim Gust, Maia Hamin, Kat He, Klaudia Krawiecka, Riccardo Patana, Neil Perry, Troy Peterson, Xiangyu Qi, Javier Rando, Zifan Wang, Zihan Wang, Spencer Whitman, Eric Winsor, Arman Zharmagambetov, Matt Fredrikson, Zico Kolter

CoRR, March, 2026

2025

Safety Alignment of LMs via Non-cooperative Games.

Anselm Paulus, Ilia Kulikov, Brandon Amos, Rémi Munos, Ivan Evtimov, Kamalika Chaudhuri, Arman Zharmagambetov

CoRR, December, 2025

CIMemories: A Compositional Benchmark for Contextual Integrity of Persistent Memory in LLMs.

Niloofar Mireshghallah, Neal Mangaokar, Narine Kokhlikyan, Arman Zharmagambetov, Manzil Zaheer, Saeed Mahloujifar, Kamalika Chaudhuri

CoRR, November, 2025

RL Is a Hammer and LLMs Are Nails: A Simple Reinforcement Learning Recipe for Strong Prompt Injection.

Yuxin Wen, Arman Zharmagambetov, Ivan Evtimov, Narine Kokhlikyan, Tom Goldstein, Kamalika Chaudhuri, Chuan Guo

CoRR, October, 2025

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks.

Sizhe Chen, Arman Zharmagambetov, David A. Wagner, Chuan Guo

CoRR, July, 2025

WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks.

Ivan Evtimov, Arman Zharmagambetov, Aaron Grattafiori, Chuan Guo, Kamalika Chaudhuri

CoRR, April, 2025

AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents.

Arman Zharmagambetov, Chuan Guo, Ivan Evtimov, Maya Pavlova, Ruslan Salakhutdinov, Kamalika Chaudhuri

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?

Ori Press, Brandon Amos, Haoyu Zhao, Yikai Wu, Samuel K. Ainsworth, Dominik Krupke, Patrick Kidger, Touqir Sajed, Bartolomeo Stellato, Jisun Park, Nathanael Bosch, Eli Meril, Albert Steppi, Arman Zharmagambetov, Fangzhao Zhang, David Pérez-Piñeiro, Alberto Mercurio, Ni Zhan, Talor Abramovich, Kilian Lieret, Hanlin Zhang, Shirley Huang, Matthias Bethge, Ofir Press

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs.

Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian

Proceedings of the Forty-second International Conference on Machine Learning, 2025

MARS: Multi-radio Architecture with ML-powered Radio Selection for Mesoscale IoT Applications.

Jothi Prasanna Shanmuga Sundaram, Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa

Proceedings of the 30th IEEE International Conference on Emerging Technologies and Factory Automation, 2025

SecAlign: Defending Against Prompt Injection with Preference Optimization.

Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar, Kamalika Chaudhuri, David A. Wagner, Chuan Guo

Proceedings of the 2025 ACM SIGSAC Conference on Computer and Communications Security, 2025

2024

Aligning LLMs to Be Robust Against Prompt Injection.

Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar, Kamalika Chaudhuri, Chuan Guo

CoRR, 2024

MARS: Multi-radio Architecture with Radio Selection using Decision Trees for emerging mesoscale CPS/IoT applications.

Jothi Prasanna Shanmuga Sundaram, Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán, Alberto Cerpa

CoRR, 2024

Contrastive Predict-and-Search for Mixed Integer Linear Programs.

Taoan Huang, Aaron M. Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets.

Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GenCO: Generating Diverse Designs with Combinatorial Constraints.

Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features.

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

Proceedings of the KDD Workshop on Human-Interpretable AI 2024 co-located with 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024

To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning.

Da Ju, Song Jiang, Andrew Cohen, Aaron Foss, Sasha Mitts, Arman Zharmagambetov, Brandon Amos, Xian Li, Justine T. Kao, Maryam Fazel-Zarandi, Yuandong Tian

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

2023

GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature.

Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

CoRR, 2023

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information.

Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Better Decision Forests: Forest Alternating Optimization.

Miguel Á. Carreira-Perpiñán, Magzhan Gabidolla, Arman Zharmagambetov

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

2022

Learning Tree-Based Models with Manifold Regularization: Alternating Optimization Algorithms

Arman Zharmagambetov

PhD thesis, 2022

Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees.

Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2022

Improved Representation Learning For Acoustic Event Classification Using Tree-Structured Ontology.

Arman Zharmagambetov, Qingming Tang, Chieh-Chi Kao, Qin Zhang, Ming Sun, Viktor Rozgic, Jasha Droppo, Chao Wang

Proceedings of the IEEE International Conference on Acoustics, 2022

Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings.

Arman Serikuly Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison.

Arman Zharmagambetov, Suryabhan Singh Hada, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2021

Improved Boosted Regression Forests Through Non-Greedy Tree Optimization.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2021

Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees.

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Learning a Tree of Neural Nets.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the IEEE International Conference on Acoustics, 2021

Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Smaller, more accurate regression forests using tree alternating optimization.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the 37th International Conference on Machine Learning, 2020

Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting.

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

2019

An Experimental Comparison of Old and New Decision Tree Algorithms.

Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán

CoRR, 2019

2016

On One Approach of Solving Sentiment Analysis Task for Kazakh and Russian Languages Using Deep Learning.

Narynov Sergazy Sakenovich, Arman Serikuly Zharmagambetov

Proceedings of the Computational Collective Intelligence - 8th International Conference, 2016