33 citations · 99 across the 9 of their papers we have counts for
9 papers
How Do Agents Fail on AutoResearch: End-to-End Diagnostic Evaluation on 100 Real-World Frontier Research Tasks
Yanlin Fei, Nazhou Liu, Xinmiao Yu +7
AI has long assisted scientific research, but the rapid advance of LLMs and agentic scaffolds is reshaping the landscape; a single system can now carry whole-stage research from an…
Reconstruction: A Blind Benchmark for Recovering Research Ideas from Pre-Publication Bibliographies
Shaolong Chen, Yanlin Fei, Nazhou Liu +7
Can a language model recover the true research idea of a published paper when given only that paper's pre-publication bibliography? We introduce Reconstruction, a blind idea-recove…
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records
Scott L. Fleming, Alejandro Lozano, William J. Haberkorn +27
The ability of large language models (LLMs) to follow natural language instructions with human-level fluency suggests many opportunities in healthcare to reduce administrative burd…
EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
Michael Wornow, Rahul Thapa, Ethan Steinberg +2
While the general machine learning (ML) community has benefited from public datasets, tasks, and models, the progress of ML in healthcare has been hampered by a lack of such shared…
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery
Debadutta Dash, Rahul Thapa, Juan M. Banda +15
Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our…
The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs
Michael Wornow, Yizhe Xu, Rahul Thapa +6
The successes of foundation models such as ChatGPT and AlphaFold have spurred significant interest in building similar models for electronic medical records (EMRs) to improve patie…
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record
Conor K. Corbin, Rob Maclay, Aakash Acharya +6
Machine learning (ML) applications in healthcare are extensively researched, but successful translations to the bedside are scant. Healthcare institutions are establishing framewor…
MoleHD: Ultra-Low-Cost Drug Discovery using Hyperdimensional Computing
Dongning Ma, Rahul Thapa, Xun Jiao
Modern drug discovery is often time-consuming, complex and cost-ineffective due to the large volume of molecular data and complicated molecular properties. Recently, machine learni…
HDXplore: Automated Blackbox Testing of Brain-Inspired Hyperdimensional Computing
Rahul Thapa, Dongning Ma, Xun Jiao
Inspired by the way human brain works, the emerging hyperdimensional computing (HDC) is getting more and more attention. HDC is an emerging computing scheme based on the working me…