Simulating Event-Related Potential Reading Data in a Neurally Plausible Parallel Distributed Processing Model. - Sarah Laszlo; David C. Plaut (CogSci, 2011)

Applying the dynamics of post-synaptic potentials to individual units in simulation of temporally extended ERP reading data. - Sarah Laszlo; Blair C. Armstrong (CogSci, 2013)

Putting emergence to the test: Modeling the effects of context in the time and frequency domain on the N400 Component. - Blair C. Armstrong; Sarah Laszlo (CogSci, 2014)

Brainprint: Identifying Unique Features of Neural Activity with Machine Learning. - Maria V. Ruiz-Blondet; Negin Khalifian; Blair C. Armstrong; Zhanpeng Jin; Kenneth J. Kurtz; Sarah Laszlo (CogSci, 2014)

Towards EEG biometrics: pattern matching approaches for user identification. - Qiong Gui; Zhanpeng Jin; Maria V. Ruiz-Blondet; Sarah Laszlo; Wenyao Xu (ISBA, 2015)

Assessment of permanence of non-volitional EEG brainwaves as a biometric. - Maria V. Ruiz-Blondet; Sarah Laszlo; Zhanpeng Jin (ISBA, 2015)

Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics. - Blair C. Armstrong; Maria V. Ruiz-Blondet; Negin Khalifian; Kenneth J. Kurtz; Zhanpeng Jin; Sarah Laszlo (Neurocomputing, 2015)

A residual feature-based replay attack detection approach for brainprint biometric systems. - Qiong Gui; Wei Yang; Zhanpeng Jin; Maria V. Ruiz-Blondet; Sarah Laszlo (WIFS, 2016)

CEREBRE: A Novel Method for Very High Accuracy Event-Related Potential Biometric Identification. - Maria V. Ruiz-Blondet; Zhanpeng Jin; Sarah Laszlo (IEEE Trans. Inf. Forensics Secur., 2016)

Permanence of the CEREBRE brain biometric protocol. - Maria V. Ruiz-Blondet; Zhanpeng Jin; Sarah Laszlo (Pattern Recognit. Lett., 2017)

A Survey on Brain Biometrics. - Qiong Gui; Maria V. Ruiz-Blondet; Sarah Laszlo; Zhanpeng Jin (ACM Comput. Surv., 2019)

Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting. - Su Wang 001; Chitwan Saharia; Ceslee Montgomery; Jordi Pont-Tuset; Shai Noy; Stefano Pellegrini; Yasumasa Onoe; Sarah Laszlo; David J. Fleet; Radu Soricut; Jason Baldridge; Mohammad Norouzi 002; et al. (CVPR, 2023)

Safety and Fairness for Content Moderation in Generative Models. - Susan Hao; Piyush Kumar; Sarah Laszlo; Shivani Poddar; Bhaktipriya Radharapu; Renee Shelby (CoRR, 2023)

"Is a picture of a bird a bird": Policy recommendations for dealing with ambiguity in machine vision models. - Alicia Parrish; Sarah Laszlo; Lora Aroyo (CoRR, 2023)

ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. - Akshita Jha; Vinodkumar Prabhakaran; Remi Denton; Sarah Laszlo; Shachi Dave; Rida Qadri; Chandan K. Reddy; Sunipa Dev (ACL (1), 2024)

Beyond the Surface: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. - Akshita Jha; Vinodkumar Prabhakaran; Remi Denton; Sarah Laszlo; Shachi Dave; Rida Qadri; Chandan K. Reddy; Sunipa Dev (CoRR, 2024)

Harm Amplification in Text-to-Image Models. - Susan Hao; Renee Shelby; Yuchi Liu; Hansa Srinivasan; Mukul Bhutani; Burcu Karagol Ayan; Shivani Poddar; Sarah Laszlo (CoRR, 2024)

DrawL: Understanding the Effects of Non-Mainstream Dialects in Prompted Image Generation. - Joshua Williams 001; Molly FitzMorris; Osman Aka; Sarah Laszlo (CoRR, 2024)