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Research & Development
Crafting Synthetic Medical Data: How Smart Prompts Guide AI for Privacy and Quality
TLDR: SynLLM is a new framework that uses Large Language Models (LLMs) and structured prompt engineering to generate high-quality, privacy-preserving synthetic medical tabular data....
Research & Development
Streamlining Answer Set Programming with Constant Set Reduction
TLDR: A new technique called "diminution" is introduced to tackle the "grounding bottleneck" in Answer Set Programming (ASP). By selecting a smaller subset of...
Research & Development
Enhancing Clinical Decisions with Personalized, Cost-Aware Feature Selection in Electronic Health Records
TLDR: P-CAFE is a new framework that improves how we extract insights from Electronic Health Records (EHRs). It uses a personalized, step-by-step approach to...
Research & Development
Automating Communication Protocol Assessment in Training with Large Language Models
TLDR: The paper introduces "Prompt-and-Check," a method using open-source Large Language Models (LLMs) like LLaMA 3 8B to evaluate communication protocol compliance in simulation-based...
Research & Development
Aryabhata 1.0: A Specialized AI Model for Indian JEE Math Exams
TLDR: Aryabhata 1.0 is a 7B parameter language model optimized for the Indian JEE Math exam. It was developed by merging existing reasoning models,...
Research & Development
Beyond Basic AR: New Agents Learn and Remember Your Habits for Smarter Assistance
TLDR: A new framework proposes memory-augmented Augmented Reality (AR) agents that can learn from and adapt to a user's long-term experiences and preferences. By...