activity
20242026
collaborators

11 papers

cs.LG2026

Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke

Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee +8

Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) predic…

cs.CY2025

"All You Need" is Not All You Need for a Paper Title: On the Origins of a Scientific Meme

Anton Alyakin

The 2017 paper ''Attention Is All You Need'' introduced the Transformer architecture-and inadvertently spawned one of machine learning's most persistent naming conventions. We anal…

cs.CL2025

Generalist Large Language Models Outperform Clinical Tools on Medical Benchmarks

Krithik Vishwanath, Mrigayu Ghosh, Anton Alyakin +3

Specialized clinical AI assistants are rapidly entering medical practice, often framed as safer or more reliable than general-purpose large language models (LLMs). Yet, unlike fron…

cs.AI2025

CNS-Obsidian: A Neurosurgical Vision-Language Model Built From Scientific Publications

Anton Alyakin, Jaden Stryker, Daniel Alexander Alber +29

General-purpose VLMs demonstrate impressive capabilities, but their opaque training on uncurated internet data poses critical limitations for high-stakes decision-making, such as i…

cs.CL2025

Generalist Foundation Models Are Not Clinical Enough for Hospital Operations

Lavender Y. Jiang, Angelica Chen, Xu Han +16

Hospitals and healthcare systems rely on operational decisions that determine patient flow, cost, and quality of care. Despite strong performance on medical knowledge and conversat…

cs.CL2025

MedMobile: A mobile-sized language model with clinical capabilities

Krithik Vishwanath, Jaden Stryker, Anton Alyakin +2

Language models (LMs) have demonstrated expert-level reasoning and recall abilities in medicine. However, computational costs and privacy concerns are mounting barriers to wide-sca…