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Pengenalan prompt engineering [PDF]
Buku Pengenalan Prompt Engineering memberikan pandangan mendalam tentang konsep dan aplikasi teknik prompt dalam dunia komputasi. Penulis membahas secara rinci penggunaan dan manfaat dari prompt engineering, sebuah pendekatan yang semakin populer dalam ...
Yulius Denny Prabowo +2 more
core
Cancer progression is regulated by the dynamic matrix code of the tumor microenvironment, which influences cellular behavior and disease development. Importantly, matrix remodeling in three‐dimensional cancer models more accurately reflects in vivo conditions compared to conventional two‐dimensional systems.
Sylvia Mangani +3 more
wiley +1 more source
KI Prompt Engineering Strategien [PDF]
Eine Sammlung von Prompt Engineering Tipps für Large Language ...
Tjark Müller
core
Semiotics-based prompt engineering for architectural text-to-image generation processes
Text-to-image generative AI tools have gained significant attention in the architectural community; however, they are currently being used by trial-and-error with simple textual inputs.
Şule Taşlı Pektaş, Bilge Sağlam
doaj +1 more source
Prompt Engineering for evaluators: optimizing LLMs to judge linguistic proficiency
Prompt Engineering, the practice of optimizing the question made to a Large Language Model, is closely linked to the evaluation procedures. Depending on the type of task we are performing through LLMs, we can have an evaluation metric with high or low ...
Lorenzo Gregori
doaj +1 more source
The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi +6 more
wiley +1 more source
A Novel Llama 3-Based Prompt Engineering Platform for Textual Data Generation and Labeling [PDF]
With the growing demand for labeled textual data in Natural Language Processing (NLP), traditional data collection and annotation methods face significant challenges, such as high cost, limited scalability, and privacy constraints.
Wedyan Salem Alsakran +1 more
core +1 more source
MED-Prompt: A novel prompt engineering framework for medicine prediction on free-text clinical notes
Existing AI-based medicine prediction systems require substantial training time, computing resources, and extensive labeled data, yet they often lack scalability.
Awais Ahmed +4 more
doaj +1 more source
Probing Maximally Divergent Conceptual Regions in Large Language Models Through Prompt Engineering [PDF]
Large Language Models (LLMs) have shown impressive capabilities in natural language understanding and reasoning; however, their internal conceptual organization remains largely opaque.
Davut Çulha
doaj +3 more sources
Prompt Less, Smile More: MTP with Semantic Engineering in Lieu of Prompt Engineering
AI-Integrated programming is emerging as a foundational paradigm for building intelligent systems with large language models (LLMs). Recent approaches such as Meaning Typed Programming (MTP) automate prompt generation by leveraging the semantics already present in code.
Jayanaka L. Dantanarayana +6 more
openaire +2 more sources

