2 papers
cs.CL2025
SAFE: Improving LLM Systems using Sentence-Level In-generation Attribution
João Eduardo Batista, Emil Vatai, Mohamed Wahib
Large Language Models (LLMs) are increasingly applied in various science domains, yet their broader adoption remains constrained by a critical challenge: the lack of trustworthy, v…
cs.LG2025
Embedding Domain-Specific Knowledge from LLMs into the Feature Engineering Pipeline
João Eduardo Batista
Feature engineering is mandatory in the machine learning pipeline to obtain robust models. While evolutionary computation is well-known for its great results both in feature select…