Research on quantitative evaluation method of goal conflict in multimodal scenarios
Harnessing multimodal data for real-time conflict analysis and resolution solutions.
Innovative Solutions for Target Conflicts
We specialize in data collection, model fine-tuning, and framework development to effectively identify and resolve target conflicts in various multimodal scenarios.
Data Collection
Gather comprehensive datasets of multimodal scenarios that showcase various target conflicts and challenges.
Model Fine-Tuning
Enhance GPT-4 capabilities for identifying and analyzing target conflicts through advanced fine-tuning techniques.
Data Collection
Gathering multimodal datasets for conflict analysis and resolution.
Model Fine-tuning
Optimizing GPT-4 for enhanced conflict detection and analysis.
Expected Outcomes
This research aims to demonstrate that fine-tuning GPT-4 can significantly enhance the ability to quantitatively assess and resolve target conflicts in multimodal scenarios. The outcomes will contribute to a deeper understanding of how advanced AI models can be adapted for complex, real-world applications, improving decision-making and conflict resolution efficiency. Additionally, the study will highlight the societal impact of AI in fostering safer, more reliable systems, reducing errors, and supporting ethical AI deployment.