Matthew L. Olson

According to our database, Matthew L. Olson authored at least 31 papers between 2018 and 2026.

Collaborative distances:

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

2026

Co-Evolving LLM Decision and Skill Bank Agents for Long-Horizon Tasks.

Xiyang Wu, Zongxia Li, Guangyao Shi, Alexander Duffy, Tyler Marques, Matthew Lyle Olson, Tianyi Zhou, Dinesh Manocha

CoRR, April, 2026

Data-Centric Interpretability for LLM-based Multi-Agent Reinforcement Learning.

John Yan, Michael Yu, Yuqi Sun, Alexander Duffy, Tyler Marques, Matthew Lyle Olson

CoRR, February, 2026

LieCraft: A Multi-Agent Framework for Evaluating Deceptive Capabilities in Language Models.

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Tri Nguyen, Vasudev Lal, Joseph Campbell, Simon Stepputtis, Shao-Yen Tseng

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Democratizing Diplomacy: A Harness for Evaluating Any Large Language Model on Full-Press Diplomacy.

Alexander Duffy, Samuel J. Paech, Ishana Shastri, Elizabeth Karpinski, Baptiste Alloui-Cros, Tyler Marques, Matthew Lyle Olson

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Bayesian Social Deduction with Graph-Informed Language Models.

Shahab Rahimirad, Guven Gergerli, Lucia Romero, Angela Qian, Matthew Lyle Olson, Simon Stepputtis, Joseph Campbell

CoRR, June, 2025

Semantic Specialization in MoE Appears with Scale: A Study of DeepSeek R1 Expert Specialization.

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Man Luo, Sungduk Yu, Chendi Xue, Vasudev Lal

CoRR, February, 2025

BLIP-3: A Family of Open Large Multimodal Models.

Le Xue, Manli Shu, Anas Awadalla, Jun Wang, An Yan, Senthil Purushwalkam, Honglu Zhou, Viraj Prabhu, Yutong Dai, Michael S. Ryoo, Shrikant Kendre, Jieyu Zhang, Shao-Yen Tseng, Gustavo A. Lujan-Moreno, Matthew L. Olson, Musashi Hinck, David Cobbley, Vasudev Lal, Can Qin, Shu Zhang, Chia-Chih Chen, Ning Yu, Juntao Tan, Tulika Manoj Awalgaonkar, Shelby Heinecke, Huan Wang, Yejin Choi, Ludwig Schmidt, Zeyuan Chen, Silvio Savarese, Juan Carlos Niebles, Caiming Xiong, Ran Xu

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

Debias Your Large Multi-Modal Model at Test-Time via Non-Contrastive Visual Attribute Steering.

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

Probing the Representational Power of Sparse Autoencoders in Vision Models.

Matthew L. Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

Probing Semantic Routing in Large Mixture-of-Expert Models.

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Man Luo, Sungduk Yu, Chendi Xue, Vasudev Lal

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders.

Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data.

Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh

Mach. Learn. Sci. Technol., 2024

Steering Large Language Models to Evaluate and Amplify Creativity.

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal

CoRR, 2024

Debias your Large Multi-Modal Model at Test-Time with Non-Contrastive Visual Attribute Steering.

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Estelle Aflalo, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

CoRR, 2024

Super-Resolution without High-Resolution Labels for Black Hole Simulations.

Thomas Helfer, Thomas D. P. Edwards, Jessica Dafflon, Kaze W. K. Wong, Matthew Lyle Olson

CoRR, 2024

Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations.

Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard

CoRR, 2024

ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution.

Sungduk Yu, Brian L. White, Anahita Bhiwandiwalla, Musashi Hinck, Matthew Lyle Olson, Tung Nguyen, Vasudev Lal

CoRR, 2024

LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model.

Musashi Hinck, Matthew L. Olson, David Cobbley, Shao-Yen Tseng, Vasudev Lal

CoRR, 2024

AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making.

Shusen Liu, Haichao Miao, Zhimin Li, Matthew L. Olson, Valerio Pascucci, Peer-Timo Bremer

Comput. Graph. Forum, 2024

LVLM-Intrepret: An Interpretability Tool for Large Vision-Language Models.

Gabriela Ben Melech Stan, Estelle Aflalo, Raanan Yehezkel Rohekar, Anahita Bhiwandiwalla, Shao-Yen Tseng, Matthew Lyle Olson, Yaniv Gurwicz, Chenfei Wu, Nan Duan, Vasudev Lal

Proceedings of the 3rd Explainable AI for Computer Vision (XAI4CV) Workshop, 2024

Why do LLaVA Vision-Language Models Reply to Images in English?

Musashi Hinck, Carolin Holtermann, Matthew L. Olson, Florian Schneider, Sungduk Yu, Anahita Bhiwandiwalla, Anne Lauscher, Shao-Yen Tseng, Vasudev Lal

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models.

Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong

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

GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations.

Tobias Huber, Maximilian Demmler, Silvan Mertes, Matthew L. Olson, Elisabeth André

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Deep Generative Multimedia Children's Literature.

Matthew L. Olson

CoRR, 2022

How Do People Rank Multiple Mutant Agents?

Jonathan Dodge, Andrew Anderson, Matthew L. Olson, Rupika Dikkala, Margaret Burnett

Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22, 2022

2021

Counterfactual state explanations for reinforcement learning agents via generative deep learning.

Matthew L. Olson, Roli Khanna, Lawrence Neal, Fuxin Li, Weng-Keen Wong

Artif. Intell., 2021

Contrastive Identification of Covariate Shift in Image Data.

Matthew L. Olson, Thuy-Vy Nguyen, Gaurav Dixit, Neale Ratzlaff, Weng-Keen Wong, Minsuk Kahng

Proceedings of the 2021 IEEE Visualization Conference, 2021

2020

Mental Models of Mere Mortals with Explanations of Reinforcement Learning.

Andrew Anderson, Jonathan Dodge, Amrita Sadarangani, Zoe Juozapaitis, Evan Newman, Jed Irvine, Souti Chattopadhyay, Matthew L. Olson, Alan Fern, Margaret Burnett

ACM Trans. Interact. Intell. Syst., 2020

2019

Counterfactual States for Atari Agents via Generative Deep Learning.

Matthew L. Olson, Lawrence Neal, Fuxin Li, Weng-Keen Wong

CoRR, 2019

2018

Reduce Before You Localize: Delta-Debugging and Spectrum-Based Fault Localization.

Arpit Christi, Matthew Lyle Olson, Mohammad Amin Alipour, Alex Groce

Proceedings of the 2018 IEEE International Symposium on Software Reliability Engineering Workshops, 2018

Open Set Learning with Counterfactual Images.

Lawrence Neal, Matthew L. Olson, Xiaoli Z. Fern, Weng-Keen Wong, Fuxin Li

Proceedings of the Computer Vision - ECCV 2018, 2018