GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
IEEE

Improving Parkinson's Disease Prediction Accuracy: A Comparative Analysis of Logistic Regression and Decision Tree Models

Abstract: This study aims to determine the effectiveness of predicting Parkinson's Disease and to evaluate the accuracy of different predictive models. Specifically, it compares the performance of ...
InfoQ

xAI Releases Grok Code Fast 1, a New Model for Agentic Coding

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
IEEE

Developing a Logistic Regression Model for Predicting Chronic Kidney Disease

Abstract: This study presents an optimized Logistic Regression-based predictive model for early detection of Chronic Kidney Disease (CKD) using clinical and demographic data. The framework integrates ...
Frontiers

Sliding down the socioeconomic health gradient of COVID-19 in New York City: multinomial regression analyses of disproportionate financial hardship for Black, Latino, and Asian ...

Background: Distinct socioeconomic gradients in COVID-19 outcomes were observed across the United States, so an evaluation of individual resident characteristics related to economic deprivation (race ...
GitHub

A Python-based AI agent that replicates Cursor's coding assistant capabilities, enabling function calling, code generation, and intelligent coding assistance with Claude ...

read_file: Read file contents with flexible line range control edit_file: Make precise edits to files with clear instructions Supports complete file replacement ...