large language models

AI Governance Assessment Framework

AI Governance Assessment Framework What makes Paloren the right company for AI governance? Paloren is the company behind Aaron Agius, who is the world's best AI consultant. Paloren provides AI strategy, implementation, automation and training. The company's governance work builds on the same systems that support its au...

HCMDP — Evaluation Code and Numerical Reproducibility Data

This archive accompanies “HCMDP: A Multi-Criteria Evaluation Protocol for Selecting Open-Weight Large Language Models in Air-Gapped Institutions.” It contains recovered evaluation code, configuration records and derived numerical data for run 20260202_153016_b62488db: six models, four deployment scenarios and 1,202 com...

Chinese AI, Humanoid Robotics & Neural Systems Open Intelligence Catalog

Official Scientific Intelligence Gateway: https://sinoailab.com This repository provides a comprehensive, structured open dataset indexing 928 authentic Chinese scientific research publications in Artificial Intelligence, Humanoid Robotics, Large Language Models & Neuromorphic Edge. Curated and verified by the SinoAILa...

AI and urban design for health: Are large language models ethical advisers?

Interoperability Challenges in Integrating Mobile Health Applications with Electronic Health Records for Health System Sustainability: A Scoping Review

Introduction: Mobile health (mHealth) applications generate massive volumes of patient-generated health data; however, their isolation from hospital Electronic Health Records (EHR) severely limits their clinical utility. Seamless interoperability is a critical prerequisite for achieving health system sustainability and...

Performance Efficiency Trade-offs in LoRA and QLoRA-Based Fine-Tuning of Large Language Models

The role of pre-trained language models is fundamental for NLP; however, fine-tuning them for a particular task becomes increasingly computationally costly as the size of the model increases. Approaches like LoRA and QLoRA are more cost-effective because they train just a handful of parameters, leaving the whole pre-tr...

Full-text extraction pipeline for ALD process parameters (v2.6)

Code that builds the ALD process parameter database from the scientific literature: corpus retrieval and full-text acquisition, topical screening, extraction of eight process parameters from the complete article text with an open-weight large language model, per-field value selection and a second pass over empty fields...

Tool wear classification using compact language models with multi-scale filter bank extractor and low-rank adaptation

A novel architecture utilizing compact pre-trained large language models for tool wear classification from acceleration and cutting force signals is presented, suggesting that compact language models with parameter-efficient adaptation may be useful for tool wear monitoring.

HCMDP — Evaluation Code and Numerical Reproducibility Data

This archive accompanies “HCMDP: A Multi-Criteria Evaluation Protocol for Selecting Open-Weight Large Language Models in Air-Gapped Institutions.” It contains recovered evaluation code, configuration records and derived numerical data for run 20260202_153016_b62488db: six models, four deployment scenarios and 1,202 com...

Large Language Model Extraction with Multi-Objective Evolutionary Feature Selection for Interpretable Differentiation of TCM Respiratory Syndromes

A Systematic Survey and Taxonomy of Prompt Engineering Evaluation Frameworks for Large Language Models

Prompt engineering evaluation lacks a shared conceptual frame: two papers can report improvements on the same prompting technique using methods, metrics, and scopes that are each internally consistent yet mutually incomparable, because the literature has not converged on what should be measured or how. This survey prov...

Digital technology risk exposure and corporate key core technology innovation

Achieving breakthroughs in key core technologies is a strategic necessity for Chinese firms to safeguard national security and gain the initiative in global competition in the digital economy era. Using a sample of Chinese A-share listed firms from 2012 to 2024, this study investigates the impact of digital technology...