IEEE

Integrating Model-Agnostic Meta-Learning with Advanced Language Embeddings for Few-Shot Intent Classification

Abstract: Addressing the challenge of few-shot learning in intent classification tasks within Natural Language Processing (NLP), this study introduces a novel approach that harnesses the robust ...
IEEE

Evaluating the Effectiveness of Advanced Language Models in Detecting and Mitigating Hallucinations Using Structured Question- Answering, Novel Metrics, and Post-Hoc Retrieval

Abstract: In the rapidly evolving field of Artificial Intelligence (AI), Large Language Models (LLMs) have demonstrated significant potential across various Natural Language Processing (NLP) ...