Work

Cross-sectional analysis of large language models in current natural language generation challenges

Year: 2026

Type: article

Abstract: • Longitudinal analysis of 5 large language model families and their versions over time. • Newer model versions and larger size do not always improve task-specific capabilities. • Expert-set thresholds enable accurate evaluation of responses for each research gap. • Analysis method is reproducible and adaptable to other languages and available models.

Source: Information Processing & Management

DOI: 10.1016/j.ipm.2026.104922

Authors: María Miró Maestre, Iván Martínez-Murillo, Aitana Morote Martínez, Elena Lloret

Institution: University of Alicante

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,670