Cover Image

Waking Up an AI: A Quantitative Framework for Prompt-Induced Phase Transition in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Sato, Makoto
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Triggering Hallucinations in LLMs: A Quantitative Study of Prompt-Induced Hallucination in Large Language Models
by: Sato, Makoto
Published: (2025)

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation
by: Sato, Makoto
Published: (2026)

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure
by: Cook, David A.
Published: (2026)

Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models
by: Murthy, Rithesh, et al.
Published: (2025)

The Way We Prompt: Conceptual Blending, Neural Dynamics, and Prompt-Induced Transitions in LLMs
by: Sato, Makoto
Published: (2025)

PromptBridge: Cross-Model Prompt Transfer for Large Language Models
by: Wang, Yaxuan, et al.
Published: (2025)

UtilityMax Prompting: A Formal Framework for Multi-Objective Large Language Model Tasks
by: Marom, Ofir
Published: (2026)

Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models
by: Tan, Wenting, et al.
Published: (2024)

Are Large Language Models Good Prompt Optimizers?
by: Ma, Ruotian, et al.
Published: (2024)

Large Language Models Prompting With Episodic Memory
by: Do, Dai, et al.
Published: (2024)

On the Worst Prompt Performance of Large Language Models
by: Cao, Bowen, et al.
Published: (2024)

Evidence of Phase Transitions in Small Transformer-Based Language Models
by: Hong, Noah, et al.
Published: (2025)

Large Language Models are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales
by: Kwon, Taeyoon, et al.
Published: (2023)

Intelligent Understanding of Large Language Models in Traditional Chinese Medicine Based on Prompt Engineering Framework
by: Chen, Yirui, et al.
Published: (2024)

Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks
by: Mu, Lin, et al.
Published: (2025)

Diverse Prompts: Illuminating the Prompt Space of Large Language Models with MAP-Elites
by: Santos, Gabriel Machado, et al.
Published: (2025)

Phase Transitions in the Output Distribution of Large Language Models
by: Arnold, Julian, et al.
Published: (2024)

Follow-Up Questions Improve Documents Generated by Large Language Models
by: Tix, Bernadette J
Published: (2024)

Towards Generalist Prompting for Large Language Models by Mental Models
by: Guan, Haoxiang, et al.
Published: (2024)

Prompt and Parameter Co-Optimization for Large Language Models
by: Bo, Xiaohe, et al.
Published: (2025)

Prompt-based Depth Pruning of Large Language Models
by: Wee, Juyun, et al.
Published: (2025)

Prompt-Based Value Steering of Large Language Models
by: Abbo, Giulio Antonio, et al.
Published: (2025)

An Empirical Study on Prompt Compression for Large Language Models
by: Zhang, Zheng, et al.
Published: (2025)

Metacognitive Prompting Improves Understanding in Large Language Models
by: Wang, Yuqing, et al.
Published: (2023)

Unveiling and Manipulating Prompt Influence in Large Language Models
by: Feng, Zijian, et al.
Published: (2024)

Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework
by: Sun, Qiao, et al.
Published: (2024)

DROJ: A Prompt-Driven Attack against Large Language Models
by: Hu, Leyang, et al.
Published: (2024)

Bangla AI: A Framework for Machine Translation Utilizing Large Language Models for Ethnic Media
by: Goni, MD Ashraful, et al.
Published: (2024)

How Confident Is the First Token? An Uncertainty-Calibrated Prompt Optimization Framework for Large Language Model Classification and Understanding
by: Chen, Wei, et al.
Published: (2026)

Anti-adversarial Learning: Desensitizing Prompts for Large Language Models
by: Li, Xuan, et al.
Published: (2025)

Dynamic Compressing Prompts for Efficient Inference of Large Language Models
by: Hu, Jinwu, et al.
Published: (2025)

Continual Learning Using Only Large Language Model Prompting
by: Qiu, Jiabao, et al.
Published: (2024)

ExpertPrompting: Instructing Large Language Models to be Distinguished Experts
by: Xu, Benfeng, et al.
Published: (2023)

Large Language Models Vote: Prompting for Rare Disease Identification
by: Oniani, David, et al.
Published: (2023)

Prompting Large Language Models for Supporting the Differential Diagnosis of Anemia
by: Castagnari, Elisa, et al.
Published: (2024)

Prompt Programming for Cultural Bias and Alignment of Large Language Models
by: Eren, Maksim, et al.
Published: (2026)

Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Models
by: Castillo-Bolado, David, et al.
Published: (2024)

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
by: Zollo, Thomas P., et al.
Published: (2023)

BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting
by: Wang, Zhensheng, et al.
Published: (2026)

OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting
by: Liu, Xukai, et al.
Published: (2024)