Papers Prompt Engineering
“Prompt Engineering” 태그가 달린 논문 1,875편 · 필터 해제
A Multi-Agent System for Autonomous, Fine-Tuning-Free Clinical Symptom Detection: Development and Validation Study
Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extraction approaches either rely on context-insensitive rules that gener…
Prompt EngineeringFrom Application-Layer Simulation to Native Meta-Architecture: Structural Tension as an Endogenous Driver for Heterogeneous AI Evolution
Current large language models (LLMs) are stateless across inference sessions: their behavior is fully determined by input at inference time, and any higher-order cognitive architecture must be simulated at the applicatio…
Prompt EngineeringPrompting Complexity: Shortest Prompts for Texts and Behaviors in LLMs
In this paper, we define the quantity of prompting complexity: for a fixed instruction-tuned language model, what is the shortest plausible prompt that makes deterministic decoding produce a target text? It is an LM-rela…
Prompt EngineeringPrompt Coach: An Empirical Evaluation of an Agentic Tutor for Learning Prompt Engineering in Software Development
Prompt engineering has emerged as a critical yet undertaught skill for software developers, one that traditional learning approaches are ill-equipped to support given its evolving, interactive, and context-dependent natu…
Prompt EngineeringCSTutorBench: Benchmarking Small Language Models as Tutors for Block-Based Programming
Large language models are increasingly explored as AI tutors, yet deploying them in K-12 settings raises concerns around privacy, cost, and reliance on proprietary models. Small language models (SLMs) offer a promising a…
Prompt EngineeringAgentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions
The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intelligence, cybersecurity, and cyber investigation. Large language models…
Adversarial RobustnessPrompt EngineeringQuestion AnsweringDomain AdaptationHULAT2 at MER-TRANS 2026: Governed Multi-Agent Simplification for Spanish Easy-to-Read Generation
This paper describes the participation of HULAT2-UC3M in the Spanish track of MER-TRANS 2026, a shared task on multilingual Easy-to-Read translation. Three fully automatic Spanish runs were submitted. RUN1 and RUN2 used …
Prompt EngineeringQWERTY: Training-Free Motion Control via Query-Warped Video Diffusion Transformers
Video diffusion transformers (DiTs) generate high-fidelity and temporally coherent videos, yet motion control remains implicit, primarily relying on text prompts. As a result, achieving desired motion often requires exte…
Prompt EngineeringPost-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting
Recent generative models can produce high-quality synthetic images, offering scalable training training data for data-hungry models. Existing approaches to exploiting this potential typically involve 1) training or fine-…
Prompt EngineeringHidden-Shot: Towards One-Shot Task Generalization for Low-Level Vision Generalist Models
Despite the intense engagement surrounding low-level vision generalist models, their effectiveness in zero/few-shot scenarios beyond learned tasks remains unverified. The primary challenge of developing an ideal generali…
Prompt EngineeringAdaptive Perturbation Selection for Contrastive Audio Decoding
Large audio-language models (LALMs) frequently hallucinate by overriding acoustic evidence with language priors. While contrastive decoding (CD) offers training-free mitigation, existing methods rely on blunt perturbatio…
Prompt EngineeringDistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articles
We present DistilledGemma, an efficient and accurate system for the HIPE-2026 shared task on person-place relation extraction from multilingual historical newspaper articles in English, German, and French. Our approach a…
Computational EfficiencyKnowledge DistillationRelation ExtractionPrompt EngineeringMechanistic Personality Analysis of LLMs Steering Personality via Latent Feature Interventions
Large Language Models (LLMs) have demonstrated the ability to simulate human-like OCEAN personality traits in generated text. Previous efforts have focused on prompt engineering or fine-tuning to shape LLM personality. I…
Prompt EngineeringAI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach
The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for structured information extraction. Traditional approaches to Product Attribu…
Attribute Value ExtractionInformation ExtractionPrompt EngineeringMatching Tasks to Objectives: Fine-Tuning and Prompt-Tuning Strategies for Encoder-Decoder Pre-trained Language Models
Prompt-based learning has emerged as a dominant paradigm in natural language processing. This study explores the impact of diverse pre-training objectives on the performance of encoder-decoder pre-trained language models…
Prompt EngineeringQuestion AnsweringLLM-Aided A* Search in Non-Geometric Network Graphs
Finding the shortest path in non-geometric network graphs, where edge weights encode arbitrary metrics such as latency or monetary cost rather than spatial distance, poses a challenge for informed search algorithms. Thei…
Prompt EngineeringLeveraging Large Language Models to Obscure Code Stylometry: A Comparative Study of GPT-3.5 and GPT-4
In the rapidly evolving field of software development, code stylometry analyzing unique stylistic signatures of programmers plays a crit-ical role in authorship attribution and cybersecurity. Recent advancements in artif…
Prompt EngineeringPeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality
As academic submissions grow, the traditional peer review process struggles to keep up, raising concerns about quality and fairness. A trend of using large language models (LLMs) for assistance has emerged. In this work,…
Prompt EngineeringPROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs
Medical vision-language models (VLMs) enable zero-shot clinical image classification, yet reliably detecting out-of-distribution (OOD) inputs at deployment remains an open problem. No static scoring method works across a…
Image ClassificationPrompt EngineeringLLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline
Generative AI and large language models (LLMs) are increasingly applied to question generation and automated assessment. However, deploying LLMs in preparation for high-stakes exams requires more than prompt engineering;…
Question GenerationPrompt Engineering