collaborators

10 papers

cs.CV2026

Real-time Reconstruction of Human Visual Perception from fMRI

Rishab S. Iyer, Jiaxin Cindy Tu, Cesar Kadir Torrico Villanueva +10

Real-time closed-loop neurofeedback based on functional magnetic resonance imaging (fMRI) has led to important scientific and clinical advances. However, the sophistication of the…

cs.LG2026

Compress-Distill: Reasoning Trace Compression for Efficient Knowledge Distillation

Maxime Griot, Paul Steven Scotti, Tanishq Mathew Abraham

Reasoning models produce long chain-of-thought traces that are costly to distill and encourage verbose student outputs. We study post-hoc compression of such traces before knowledg…

q-bio.NC2026

MIRAGE: Robust multi-modal architectures translate fMRI-to-image models from vision to mental imagery

Reese Kneeland, Cesar Kadir Torrico Villanueva, Jordyn Ojeda +4

To be useful for downstream applications, vision decoding models that are trained to reconstruct seen images from human brain activity must be able to generalize to internally gene…

cs.CV2026

Scaling Vision Transformers for Functional MRI with Flat Maps

Connor Lane, Mihir Tripathy, Leema Krishna Murali +15

We study the problem of training self-supervised foundation models for functional MRI. Our main contributions are: (1) we introduce a new model family (CortexMAE) trained using the…

cs.CL2026

Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks

Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32

Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insufficient coverage of relevant…

q-bio.NC2026

ENIGMA: EEG-to-Image in 15 Minutes Using Less Than 1% of the Parameters

Reese Kneeland, Wangshu Jiang, Ugo Bruzadin Nunes +3

To be practical for real-life applications, models for brain-computer interfaces must be easily and quickly deployable on new subjects, effective on affordable scanning hardware, a…