568 citations · 1.3k across the 79 of their papers we have counts for
82 papers
ReMAP: Restoring the Perceptual Cycle with Reasoning-Time Latent Visual Memory
Hao Jiang, Zhanyu Guo, Chenwei Wu +11
As multimodal large language models (MLLMs) reason for longer, attention to the initial visual input diminishes, weakening visual grounding. Visual memory reintroduces visual evide…
Testing the Black Box: Structural Barriers to Independent Evaluation of Consumer-Facing Health LLMs
Rahul Gorijavolu, Kaushik Madapati, Pritika Vig +7
Background: Consumer-facing large language models are now a common source of health information, and they interpret and personalize responses rather than retrieve them. Whether the…
Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health
Donna Tjandra, Trenton Chang, Sonali Parbhoo +8
Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurred enthusiasm in using causal…
Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering
Keshav Balakrishna, Aaryan Chityala, Vivan Kanna +6
Accurate diagnosis of neurological disorders is contingent upon advanced imaging modalities such as Magnetic Resonance Imaging (MRI), which commonly utilize sparse imaging techniqu…
Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings
Sebastian Cajas Ordóñez, Felipe Ocampo Osorio, Dax Enshan Koh +10
We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using quantum support vector machines (…
Surrogate modeling for interpreting black-box LLMs in medical predictions
Changho Han, Songsoo Kim, Dong Won Kim +4
Large language models (LLMs), trained on vast datasets, encode extensive real-world knowledge within their parameters, yet their black-box nature obscures the mechanisms and extent…