Nicholas Moratelli
I am an AI researcher working on Vision–Language and Multimodal AI, with a focus on Multimodal Large Language Models.
My research focuses on the design, training, and evaluation of
large-scale multimodal systems for
image–text understanding and multimodal reasoning, including
retrieval-augmented generation.
I have published multiple peer-reviewed papers at
top-tier venues, including CVPR, ACL and ICLR.
I am currently completing my Ph.D. in Artificial Intelligence at the AImageLab research group at the University of Modena and Reggio Emilia (defense April 2026). I recently worked as an Applied Scientist Intern at Amazon Science (Cambridge, UK), conducting research on large-scale multimodal models.
I qualified in the Italian State Examination for Engineers (Section A), granting eligibility for professional registration as an engineer in Italy.
Latest News
Publications
Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question Answering
In Conference on Computer Vision and Pattern Recognition, 2025
Causal Graphical Models for Vision-Language Compositional Understanding
In International Conference on Learning Representations 2025
Revisiting Image Captioning Training Paradigm via Direct CLIP-based Optimization
In British Machine Vision Conference 2024
Wiki-LLaVA: Hierarchical Retrieval-Augmented Generation for Multimodal LLMs
In Conference on Computer Vision and Pattern Recognition Workshops, 2024
The Revolution of Multimodal Large Language Models: A Survey
In Findings of the Association for Computational Linguistics, 2024
Fluent and Accurate Image Captioning with a Self-Trained Reward Model
In International Conference on Pattern Recognition, 2024
Positive-Augmented Contrastive Learning for Vision-and-Language Evaluation and Training
In International Journal of Computer Vision, 2025
Mitigating Hallucinations in Multimodal LLMs via Object-aware Preference Optimization
In British Machine Vision Conference 2025
LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning
In International Conference on Computer Vision, 2025
Personalizing Multimodal Large Language Models for Image Captioning: An Experimental Analysis
In European Conference on Computer Vision and Pattern Recognition, 2024
Fashion-oriented image captioning with external knowledge retrieval and fully attentive gates
In Sensors MDPI, 2023
Are Learnable Prompts the Right Way of Prompting? Adapting Vision-and-Language Models with Memory Optimization
In IEEE Intelligent Systems, 2024
Projects
LLAVA-MORE
A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning.
Get In Touch
Interested in collaboration?
I'm always open to discussing research ideas, potential collaborations, or opportunities to apply AI in innovative ways.
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