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Tag: mllms
Bibliography items where occurs: 15
- Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site
- References
- A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
5 Vision Models and Multi-Modal Large Language Models
6 Model Tuning
7 Model Evaluation and Benchmarking
8 Conclusions - A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law / 2405.01769 / ISBN:https://doi.org/10.48550/arXiv.2405.01769 / Published by ArXiv / on (web) Publishing site
- 3 Finance
- The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative / 2402.14859 / ISBN:https://doi.org/10.48550/arXiv.2402.14859 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Related Work
3. Methodology
4. Experiments - VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site
- 2 Related Works
- Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey / 2408.12880 / ISBN:https://doi.org/10.48550/arXiv.2408.12880 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Preliminaries
4 Contrastice Foundation Models (CFMs)
5 Multimodal LLMs (MLLMs)
6 Discussions of Current Studies
7 Challenges and Future Directions - Jailbreaking and Mitigation of Vulnerabilities in Large Language Models / 2410.15236 / ISBN:https://doi.org/10.48550/arXiv.2410.15236 / Published by ArXiv / on (web) Publishing site
- V. Evaluation and Benchmarking
- A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions / 2406.03712 / ISBN:https://doi.org/10.48550/arXiv.2406.03712 / Published by ArXiv / on (web) Publishing site
- IV. Improving Algorithms for Med-LLMs
- Large-scale moral machine experiment on large language models / 2411.06790 / ISBN:https://doi.org/10.48550/arXiv.2411.06790 / Published by ArXiv / on (web) Publishing site
- Discussion
- Safety at Scale: A Comprehensive Survey of Large Model Safety / 2502.05206 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- 8 Open Challenges
- From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine
/ 2502.09242 / ISBN:https://doi.org/10.48550/arXiv.2502.09242 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Methods
5 Multimodal language models in medicine - On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site
- 6 Benchmarking Large Language Models
7 Benchmarking Vision-Language Models
9 Trustworthiness in Downstream Applications
References - Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models / 2502.18505 / ISBN:https://doi.org/10.48550/arXiv.2502.18505 / Published by ArXiv / on (web) Publishing site
- 2. Methodology
- AI Automatons: AI Systems Intended to Imitate Humans / 2503.02250 / ISBN:https://doi.org/10.48550/arXiv.2503.02250 / Published by ArXiv / on (web) Publishing site
- References
- Generative AI in Transportation Planning: A Survey / 2503.07158 / ISBN:https://doi.org/10.48550/arXiv.2503.07158 / Published by ArXiv / on (web) Publishing site
- 2 Preliminaries