2 citations · 6 across the 6 of their papers we have counts for
9 papers
Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning
Asal Mehradfar, Mohammad Shahab Sepehri, Owen Antholine +4
Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after systemic administration. Redirect…
MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI
Paula Arguello, Berk Tinaz, Mohammad Shahab Sepehri +2
Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been driven largely by public datas…
ATHENA: Adaptive Test-Time Steering for Improving Count Fidelity in Diffusion Models
Mohammad Shahab Sepehri, Asal Mehradfar, Berk Tinaz +2
Text-to-image diffusion models achieve high visual fidelity but surprisingly exhibit systematic failures in numerical control when prompts specify explicit object counts. To addres…
ConceptMix++: Leveling the Playing Field in Text-to-Image Benchmarking via Iterative Prompt Optimization
Haosheng Gan, Berk Tinaz, Mohammad Shahab Sepehri +2
Current text-to-image (T2I) benchmarks evaluate models on rigid prompts, potentially underestimating true generative capabilities due to prompt sensitivity and creating biases that…
Hyperphantasia: A Benchmark for Evaluating the Mental Visualization Capabilities of Multimodal LLMs
Mohammad Shahab Sepehri, Berk Tinaz, Zalan Fabian +1
Mental visualization, the ability to construct and manipulate visual representations internally, is a core component of human cognition and plays a vital role in tasks involving re…
A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction
Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato +4
The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a major bottleneck in RNA therapeutics development. Recent advances demon…
CryptoMamba: Leveraging State Space Models for Accurate Bitcoin Price Prediction
Mohammad Shahab Sepehri, Asal Mehradfar, Mahdi Soltanolkotabi +1
Predicting Bitcoin price remains a challenging problem due to the high volatility and complex non-linear dynamics of cryptocurrency markets. Traditional time-series models, such as…
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models
Mohammad Shahab Sepehri, Zalan Fabian, Maryam Soltanolkotabi +1
Multimodal Large Language Models (MLLMs) have tremendous potential to improve the accuracy, availability, and cost-effectiveness of healthcare by providing automated solutions or s…
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models
Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi
The landscape of computational building blocks of efficient image restoration architectures is dominated by a combination of convolutional processing and various attention mechanis…