Neale Ratzlaff

27 papers A* 5Journal 16Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	LieCraft: A Multi-Agent Framework for Evaluating Deceptive Capabilities in Language Models. AAAI Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Tri Nguyen, Vasudev Lal, Joseph Campbell, Simon Stepputtis, Shao-Yen Tseng
2026	J	`jnl`	LieCraft: A Multi-Agent Framework for Evaluating Deceptive Capabilities in Language Models. CoRR Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Tri Nguyen, Vasudev Lal, Joseph Campbell, Simon Stepputtis, Shao-Yen Tseng
2025	—	`conf`	Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders. CVPR Workshops Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng
2025	J	`jnl`	Analyzing Hierarchical Structure in Vision Models with Sparse Autoencoders. CoRR Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng
2025	—	`conf`	Debias Your Large Multi-Modal Model at Test-Time via Non-Contrastive Visual Attribute Steering. ICCVW Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard
2025	—	`conf`	Probing Semantic Routing in Large Mixture-of-Expert Models. EMNLP (Findings) Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Man Luo, Sungduk Yu, Chendi Xue, Vasudev Lal
2025	—	`conf`	Probing the Representational Power of Sparse Autoencoders in Vision Models. ICCVW Matthew L. Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng
2025	J	`jnl`	Probing the Representational Power of Sparse Autoencoders in Vision Models. CoRR Matthew Lyle Olson, Musashi Hinck, Neale Ratzlaff, Changbai Li, Phillip Howard, Vasudev Lal, Shao-Yen Tseng
2025	J	`jnl`	Semantic Specialization in MoE Appears with Scale: A Study of DeepSeek R1 Expert Specialization. CoRR Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Man Luo, Sungduk Yu, Chendi Xue, Vasudev Lal
2025	—	`conf`	Training-Free Mitigation of Language Reasoning Degradation After Multimodal Instruction Tuning. AAAI Spring Symposia Neale Ratzlaff, Man Luo, Xin Su, Vasudev Lal, Phillip Howard
2024	J	`jnl`	Debias your Large Multi-Modal Model at Test-Time with Non-Contrastive Visual Attribute Steering. CoRR Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Estelle Aflalo, Shao-Yen Tseng, Vasudev Lal, Phillip Howard
2024	J	`jnl`	Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations. CoRR Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard
2024	J	`jnl`	Steering Large Language Models to Evaluate and Amplify Creativity. CoRR Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal
2024	J	`jnl`	Training-Free Mitigation of Language Reasoning Degradation After Multimodal Instruction Tuning. CoRR Neale Ratzlaff, Man Luo, Xin Su, Vasudev Lal, Phillip Howard
2023	J	`jnl`	A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
2023	J	`jnl`	A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
2021	—	`conf`	Contrastive Identification of Covariate Shift in Image Data. IEEE VIS (Short Papers) Matthew L. Olson, Thuy-Vy Nguyen, Gaurav Dixit, Neale Ratzlaff, Weng-Keen Wong, Minsuk Kahng
2021	J	`jnl`	Contrastive Identification of Covariate Shift in Image Data. CoRR Matthew L. Olson, Thuy-Vy Nguyen, Gaurav Dixit, Neale Ratzlaff, Weng-Keen Wong, Minsuk Kahng
2021	A*	`conf`	Generative Particle Variational Inference via Estimation of Functional Gradients. ICML Neale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu
2021	J	`jnl`	Generative Particle Variational Inference via Estimation of Functional Gradients. CoRR Neale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu
2020	A*	`conf`	Avoiding Side Effects in Complex Environments. NeurIPS Alexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli
2020	J	`jnl`	Avoiding Side Effects in Complex Environments. CoRR Alexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli
2020	A*	`conf`	Implicit Generative Modeling for Efficient Exploration. ICML Neale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu
2019	A*	`conf`	HyperGAN: A Generative Model for Diverse, Performant Neural Networks. ICML Neale Ratzlaff, Fuxin Li
2019	J	`jnl`	HyperGAN: A Generative Model for Diverse, Performant Neural Networks. CoRR Neale Ratzlaff, Fuxin Li
2019	J	`jnl`	Implicit Generative Modeling for Efficient Exploration. CoRR Neale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu
2018	J	`jnl`	Unifying Bilateral Filtering and Adversarial Training for Robust Neural Networks. CoRR Neale Ratzlaff, Fuxin Li