GitHub

LLMRec: Large Language Models with Graph Augmentation for Recommendation

# LLMRec python ./main.py # w/o-u-i python ./main.py --aug_sample_rate=0.0 # w/o-u python ./main.py --user_cat_rate=0 # w/o-u&i python ./main.py --user_cat_rate=0 ...
InfoWorld

How to build an AI agent that actually works

Success with agents starts with embedding them in workflows, not letting them run amok. Context, skills, models, and tools are key. There’s more.
IEEE

Balancing Security and Correctness in Code Generation: An Empirical Study on Commercial Large Language Models

Abstract: Large language models (LLMs) continue to be adopted for a multitude of previously manual tasks, with code generation as a prominent use. Multiple commercial models have seen wide adoption ...
IEEE

Model-Agnostic Empirical Evaluation of Test-Driven Prompt Engineering on Improving Accuracy and Efficiency in Large Language Models Python Code Generation

Abstract: Although Large Language Models (LLMs) are widely adopted for Python code generation, the generated code can be semantically incorrect, requiring iterations of evaluation and refinement. Test ...
GitHub

CNM-University-of-Guelph/NASEM-Model-Python

This is a python version of the Nutrient Requirments of Dairy Cattle 8th revisied edition (NASEM 2021)[https://nap.nationalacademies.org/catalog/25806/nutrient ...