Copertina

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	He, Chengyang, Zhang, Wenlong, Chen, Violet Xinying, Ning, Yue, Wang, Ping
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Understanding Student Sentiment on Mental Health Support in Colleges Using Large Language Models
di: Sood, Palak, et al.
Pubblicazione: (2024)

Large Language Model Benchmarks in Medical Tasks
di: Yan, Lawrence K. Q., et al.
Pubblicazione: (2024)

Benchmarking Large Language Models on Multiple Tasks in Bioinformatics NLP with Prompting
di: Jiang, Jiyue, et al.
Pubblicazione: (2025)

DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language Model
di: Zhao, Lirui, et al.
Pubblicazione: (2024)

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques
di: Aly, Walid Mohamed, et al.
Pubblicazione: (2025)

Using Large Language Models to Measure Symptom Severity in Patients At Risk for Schizophrenia
di: Chen, Andrew X., et al.
Pubblicazione: (2025)

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

Chinese Metaphor Recognition Using a Multi-stage Prompting Large Language Model
di: Wang, Jie, et al.
Pubblicazione: (2024)

JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese Large Language Models
di: Liu, Junyu, et al.
Pubblicazione: (2026)

Methodology of Adapting Large English Language Models for Specific Cultural Contexts
di: Zhang, Wenjing, et al.
Pubblicazione: (2024)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
di: Bedi, Suhana, et al.
Pubblicazione: (2025)

A General Highly Accurate Online Planning Method Integrating Large Language Models into Nested Rollout Policy Adaptation for Dialogue Tasks
di: Wang, Hui, et al.
Pubblicazione: (2025)

Training a Large Language Model for Medical Coding Using Privacy-Preserving Synthetic Clinical Data
di: Cook, John, et al.
Pubblicazione: (2026)

Accurate and Energy Efficient: Local Retrieval-Augmented Generation Models Outperform Commercial Large Language Models in Medical Tasks
di: Vrettos, Konstantinos, et al.
Pubblicazione: (2025)

Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models
di: Myles, Craig, et al.
Pubblicazione: (2026)

DynaCode: A Dynamic Complexity-Aware Code Benchmark for Evaluating Large Language Models in Code Generation
di: Hu, Wenhao, et al.
Pubblicazione: (2025)

$\textit{LinkPrompt}$: Natural and Universal Adversarial Attacks on Prompt-based Language Models
di: Xu, Yue, et al.
Pubblicazione: (2024)

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

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

Preference Orchestrator: Prompt-Aware Multi-Objective Alignment for Large Language Models
di: Liu, Biao, et al.
Pubblicazione: (2025)

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

Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models
di: Kapu, Nirmal Joshua, et al.
Pubblicazione: (2024)

Coding Triangle: How Does Large Language Model Understand Code?
di: Zhang, Taolin, et al.
Pubblicazione: (2025)

PACE: A Pragmatic Agent for Enhancing Communication Efficiency Using Large Language Models
di: Li, Jiaxuan, et al.
Pubblicazione: (2024)

Sparsity Induction for Accurate Post-Training Pruning of Large Language Models
di: Jiang, Minhao, et al.
Pubblicazione: (2026)

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

FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models
di: Zhu, Junyi, et al.
Pubblicazione: (2024)

Strategic Prompting for Conversational Tasks: A Comparative Analysis of Large Language Models Across Diverse Conversational Tasks
di: Joshi, Ratnesh Kumar, et al.
Pubblicazione: (2024)

A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks
di: Vatsal, Shubham, et al.
Pubblicazione: (2024)

Code-Switching In-Context Learning for Cross-Lingual Transfer of Large Language Models
di: Yoo, Haneul, et al.
Pubblicazione: (2025)

ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code
di: Tang, Xiangru, et al.
Pubblicazione: (2023)

CNNSum: Exploring Long-Context Summarization with Large Language Models in Chinese Novels
di: Wei, Lingxiao, et al.
Pubblicazione: (2024)

ELPO: Ensemble Learning Based Prompt Optimization for Large Language Models
di: Zhang, Qing, et al.
Pubblicazione: (2025)

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

Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review
di: Croxford, Emma, et al.
Pubblicazione: (2024)

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

DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Demonstration and Reasoning
di: Qiu, Hongye, et al.
Pubblicazione: (2025)

IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment
di: Zhang, Yiming, et al.
Pubblicazione: (2025)

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

FamiCom: Further Demystifying Prompts for Language Models with Task-Agnostic Performance Estimation
di: Li, Bangzheng, et al.
Pubblicazione: (2024)