Temporal and linguistic enrichment for abstractive text summarization using transformer models
This work presents a lightweight hybrid abstractive summarization model that enhances temporal awareness and linguistic flexibility, and demonstrates practical applicability for summarization systems requiring both temporal relevance and semantic robustness, while maintaining CPU efficiency and interpretability.