Year: 2025
Type: article
Abstract: This paper explores the evolving role of prompt engineering as large language models (LLMs) develop enhanced intrinsic reasoning capabilities. Initially essential for effective model performance, explicit prompting techniques are becoming less crucial with advanced models like GPT-4.5 and DeepSeek R1. Benchmark analyses indicate that intrinsic reasoning now solves most reasoning tasks efficiently, though explicit prompting still provides incremental benefits in specialized scenarios. Future directions emphasize intrinsic reasoning improvements, automated prompting strategies, and refined evaluation methods, marking a fundamental shift in leveraging LLMs.
Author: Nan Wu -
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409476722