Rethinking visual prompting for multimodal large language models with external knowledge

Rethinking visual prompting for multimodal large language models with external knowledge

In recent years, multimodal large language models (MLLMs) have made significant strides by training on vast high-quality image-text datasets, enabling them to generally understand images well. However, the inherent difficulty in explicitly conveying fine-grained or spatially dense information in tex...

Fuld beskrivelse

Bibliografiske detaljer
Main Authors:	Lin, Y, Li, Y, Chen, D, Xu, W, Clark, R, Torr, P, Yuan, L
Format:	Internet publication
Sprog:	English
Udgivet:	2024

Lignende værker

Prompting Large Language Models with Knowledge-Injection for Knowledge-Based Visual Question Answering
af: Zhongjian Hu, et al.
Udgivet: (2024-09-01)

Knowledge graph construction for heart failure using large language models with prompt engineering
af: Tianhan Xu, et al.
Udgivet: (2024-07-01)

Prompt Optimization in Large Language Models
af: Antonio Sabbatella, et al.
Udgivet: (2024-03-01)

CAT: enhancing multimodal large language model to answer questions in dynamic audio-visual scenarios
af: Ye, Q, et al.
Udgivet: (2024)

Review of large vision models and visual prompt engineering
af: Jiaqi Wang, et al.
Udgivet: (2023-11-01)

A unified prompt-based framework for few-shot multimodal language analysis
af: Xiaohan Zhang, et al.
Udgivet: (2025-06-01)

Learning visual prompts for guiding the attention of vision transformers
af: Rezaei, R, et al.
Udgivet: (2024)

REKP: Refined External Knowledge into Prompt-Tuning for Few-Shot Text Classification
af: Yuzhuo Dang, et al.
Udgivet: (2023-11-01)

Improving language model predictions via prompts enriched with knowledge graphs
af: Brate, R, et al.
Udgivet: (2023)

Aligning, autoencoding and prompting large language models for novel disease reporting
af: Liu, F, et al.
Udgivet: (2025)

uCAP: an unsupervised prompting method for vision-language models
af: Nguyen, AT, et al.
Udgivet: (2024)

Predictive Prompts with Joint Training of Large Language Models for Explainable Recommendation
af: Ching-Sheng Lin, et al.
Udgivet: (2023-10-01)

Extracting Fruit Disease Knowledge from Research Papers Based on Large Language Models and Prompt Engineering
af: Yunqiao Fei, et al.
Udgivet: (2025-01-01)

Balancing Privacy and Robustness in Prompt Learning for Large Language Models
af: Chiyu Shi, et al.
Udgivet: (2024-10-01)

Response Generated by Large Language Models Depends on the Structure of the Prompt
af: Pradosh Kumar Sarangi, et al.
Udgivet: (2024-07-01)

Prompt Engineering: Guiding the Way to Effective Large Language Models
af: Mohammad Aljanabi, et al.
Udgivet: (2023-11-01)

An image is worth 1000 lies: adversarial transferability across prompts on vision-language models
af: Luo, H, et al.
Udgivet: (2024)

A Brief Overview of Few-Shot Prompting in the Large Language Models
af: Vladlen Kulikov, et al.
Udgivet: (2023-05-01)

Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine
af: Thomas Savage, et al.
Udgivet: (2024-01-01)

The application of multimodal large language models in medicine
af: Jianing Qiu, et al.
Udgivet: (2024-04-01)

Clinical prompt learning with frozen language models
af: Taylor, N, et al.
Udgivet: (2023)

LLMR: Real-time Prompting of Interactive Worlds using Large Language Models
af: De La Torre, Fernanda, et al.
Udgivet: (2024)

Large language model enhanced with prompt-based vanilla distillation for sentence embeddings
af: Wang, Minghao
Udgivet: (2024)

Large multimodal models for visual reasoning
af: Duong, Ngoc Yen
Udgivet: (2024)

Intelligent extraction of reservoir dispatching information integrating large language model and structured prompts
af: Yangrui Yang, et al.
Udgivet: (2024-06-01)

A Security Risk Taxonomy for Prompt-Based Interaction With Large Language Models
af: Erik Derner, et al.
Udgivet: (2024-01-01)

DetToolChain: a new prompting paradigm to unleash detection ability of MLLM
af: Wu, Y, et al.
Udgivet: (2024)

Research and application of defense mechanism for prompt injection attack of large language model in financial industry
af: MOU Daen, et al.
Udgivet: (2024-10-01)

A medical multimodal large language model for future pandemics
af: Liu, F, et al.
Udgivet: (2023)

On the legal implications of Large Language Model answers: A prompt engineering approach and a view beyond by exploiting Knowledge Graphs
af: George Hannah, et al.
Udgivet: (2025-01-01)

Rethinking Language
af: Gastor Mapunda, et al.
Udgivet: (2024-09-01)

Do Language Models Enjoy Their Own Stories? Prompting Large Language Models for Automatic Story Evaluation
af: Cyril Chhun, et al.
Udgivet: (2024-09-01)

Harnessing multimodal large language models for traffic knowledge graph generation and decision-making
af: Senyun Kuang, et al.
Udgivet: (2024-12-01)

PromptSMILES: prompting for scaffold decoration and fragment linking in chemical language models
af: Morgan Thomas, et al.
Udgivet: (2024-07-01)

The influence of knowledge visualization on externalizing tacit knowledge
af: Ahmad, Khairul Bariah, et al.
Udgivet: (2011)

Rethinking of Coase Theorem: Externalities and Uncertainty
af: Evgeny A. Kuzmin, et al.
Udgivet: (2015-10-01)

Rethinking of Coase Theorem: Externalities and Uncertainty
af: Evgeny A. Kuzmin, et al.
Udgivet: (2015-10-01)

Rethinking of Coase Theorem: Externalities and Uncertainty
af: Evgeny A. Kuzmin, et al.
Udgivet: (2015-10-01)

Rethinking of Coase Theorem: Externalities and Uncertainty
af: Evgeny A. Kuzmin, et al.
Udgivet: (2015-12-01)

TEACHING ENGLISH AS A FOREIGN LANGUAGE: RETHINKING THE MULTIMODALITY AND COMMUNICATION SKILLS IN THE 21st CENTURY
af: Liudmyla Byrkun
Udgivet: (2023-12-01)