Image de couverture de livre

An Active Inference Strategy for Prompting Reliable Responses from Large Language Models in Medical Practice

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Shusterman, Roma, Waters, Allison C., O`Neill, Shannon, Luu, Phan, Tucker, Don M.
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Multi-expert Prompting Improves Reliability, Safety, and Usefulness of Large Language Models
par: Long, Do Xuan, et autres
Publié: (2024)

Sparse Autoencoders Enable Scalable and Reliable Circuit Identification in Language Models
par: O'Neill, Charles, et autres
Publié: (2024)

Towards Reliable Truth-Aligned Uncertainty Estimation in Large Language Models
par: Srey, Ponhvoan, et autres
Publié: (2026)

Active Prompting with Chain-of-Thought for Large Language Models
par: Diao, Shizhe, et autres
Publié: (2023)

Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese
par: Wang, Haochun, et autres
Publié: (2023)

Searching for Best Practices in Medical Transcription with Large Language Model
par: Li, Jiafeng, et autres
Publié: (2024)

Towards Lightweight Reliability: Using Soft Prompts for Hallucination Mitigation in Large Language Models
par: Siddiqui, S M Tahmid, et autres
Publié: (2026)

Challenges and Responses in the Practice of Large Language Models
par: Zhu, Hongyin
Publié: (2024)

Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation
par: Ren, Zhiyao, et autres
Publié: (2026)

Dynamic Compressing Prompts for Efficient Inference of Large Language Models
par: Hu, Jinwu, et autres
Publié: (2025)

Who's Who: Large Language Models Meet Knowledge Conflicts in Practice
par: Pham, Quang Hieu, et autres
Publié: (2024)

Experimental Design for Active Transductive Inference in Large Language Models
par: Mukherjee, Subhojyoti, et autres
Publié: (2024)

On the Reliability of Large Language Models to Misinformed and Demographically-Informed Prompts
par: Aremu, Toluwani, et autres
Publié: (2024)

Inference Optimizations for Large Language Models: Effects, Challenges, and Practical Considerations
par: Donisch, Leo, et autres
Publié: (2024)

ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models
par: Qiu, Wentao, et autres
Publié: (2026)

Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models
par: Zhao, Shuai, et autres
Publié: (2023)

A New Benchmark Dataset and Mixture-of-Experts Language Models for Adversarial Natural Language Inference in Vietnamese
par: Van Huynh, Tin, et autres
Publié: (2024)

Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models
par: Zhang, Ze Yu, et autres
Publié: (2024)

Inference-Aware Prompt Optimization for Aligning Black-Box Large Language Models
par: Mahmud, Saaduddin, et autres
Publié: (2025)

Concept-Guided Chain-of-Thought Prompting for Pairwise Comparison Scoring of Texts with Large Language Models
par: Wu, Patrick Y., et autres
Publié: (2023)

The Price of Prompting: Profiling Energy Use in Large Language Models Inference
par: Husom, Erik Johannes, et autres
Publié: (2024)

Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy
par: Liu, Yijin, et autres
Publié: (2024)

Exploring the Potential of Large Language Models in Computational Argumentation
par: Chen, Guizhen, et autres
Publié: (2023)

Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies
par: Liu, Yilun, et autres
Publié: (2023)

LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs
par: Islam, K M Sajjadul, et autres
Publié: (2025)

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models
par: He, Chengyang, et autres
Publié: (2025)

ReliableMath: Benchmark of Reliable Mathematical Reasoning on Large Language Models
par: Xue, Boyang, et autres
Publié: (2025)

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
par: Zollo, Thomas P., et autres
Publié: (2023)

Transformer-Based Contextualized Language Models Joint with Neural Networks for Natural Language Inference in Vietnamese
par: Nguyen, Dat Van-Thanh, et autres
Publié: (2024)

On the Reliability of Large Language Models for Causal Discovery
par: Feng, Tao, et autres
Publié: (2024)

From Prompt Risk to Response Risk: Paired Analysis of Safety Behavior of Large Language Model
par: Hu, Mengya, et autres
Publié: (2026)

How Open Must Language Models be to Enable Reliable Scientific Inference?
par: Michaelov, James A., et autres
Publié: (2026)

PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
par: Zou, Jiaru, et autres
Publié: (2024)

Temperature-Dependent Performance of Prompting Strategies in Extended Reasoning Large Language Models
par: Salah, Mousa, et autres
Publié: (2026)

Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation
par: Sgouritsa, Eleni, et autres
Publié: (2024)

BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
par: Li, Jiangmeng, et autres
Publié: (2024)

The Muddy Waters of Modeling Empathy in Language: The Practical Impacts of Theoretical Constructs
par: Lahnala, Allison, et autres
Publié: (2025)

Evaluating Large Language Models for Anxiety, Depression, and Stress Detection: Insights into Prompting Strategies and Synthetic Data
par: Arcan, Mihael, et autres
Publié: (2025)

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors?
par: Li, Jason, et autres
Publié: (2025)

PromptDistill: Query-based Selective Token Retention in Intermediate Layers for Efficient Large Language Model Inference
par: Jin, Weisheng, et autres
Publié: (2025)