Author

Mohammad Amin Zadenoori

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Preprint Aug 2026

Predicting LLM Performance from Prompt Linguistic Features: An Empirical Study in Requirements Engineering

Whether measurable linguistic properties of prompts can predict LLM performance before inference is investigated, enabling low-cost prompt selection and refinement, validated on binary requirements classification targeting F1, F2, precision, and recall.

Quim Motger, Alessio Miaschi, Xavier Franch et al. · 1 citation

Preprint Aug 2026

Large Language Models for Requirements Engineering: A Cross-Task Empirical Evaluation

This work presents the first cross-task empirical evaluation of LLMs spanning five RE-related activities, as well as replication materials supporting reproducibility, and a broader understanding of the capabilities, limitations, and practical readiness of current LLMs for RE.

Jacek Dabrowski, Manjeshwar Aniruddh Mallya, Alessio Ferrari et al. · 1 citation