#prompt engineering
45 papers match
What makes prompts a graph: necessary and sufficient conditions for prompt graph engineering
Sandeco Macedo
The paper defines prompts as nodes in an explicit, executable graph and establishes four necessary conditions for prompt graph engineering, providing a formal definition and vocabu…
Challenges in annotations by humans and LLMs: A case study of evaluative language
Mirela Imamovic, Aenne Cecilia Kristine Knierim, Khushi Pitroda +1
The paper compares human annotators (trained linguist and trainees) with large language models on labeling evaluative language in TED talk transcripts using Appraisal theory, devel…
From Textual Requirements to Microservice Architectures - A Comprehensive Evaluation of LLM-Based Design Synthesis
Danyllo Albuquerque, José Renan, Guillermo RodrÃguez +5
The paper evaluates whether a large language model (OpenAI o3) can automatically generate microservice architectures from textual requirements, comparing zero-shot and few-shot pro…
Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning
Zheng Wu, Chenhao Xue, Shijie Zheng +3
The paper identifies a "salience bias" in large language models where explicit but irrelevant details cause the models to overlook implicit commonsense knowledge, and shows that th…
Scientific Knowledge Discovery in the Age of Large Language Models
Eleni Adamidi, Serafeim Chatzopoulos, Thanasis Vergoulis
The paper surveys 34 peer‑reviewed studies that apply generative large language models to automate scientific literature retrieval and eligibility screening, analyzing model choice…
Two Calls Beat Five Agents: Evaluating Multi-Agent Pipelines Against Self-Refinement for Local Language Models
Ashish Prajapati, Om Mohite
The paper compares a five‑role multi‑agent LLM pipeline with a simpler two‑call self‑refinement approach on a local 7B model, finding that communication format and implementation d…