Master projects
Here you can find all our available master projects.
Open Projects (12)
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[Red Cross] Low-resource Language Support
This project is offered by The Netherlands Red Cross.BackgroundThe Qualitative Feedback Analysis (QFA) project focusses on providing LLM-based intelligence to internal information-gathering tools of the Red Cross Federation. The tool supports a set of pre-defined workflows, to classify and summarize, as well as free-text …
Joaquin Vanschoren
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Dalton Harmsen
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Exploring Prompt Level Distillation as an alternative to fine-tuning for Multi-Modal Scientific Question Answering
Large Language Models use reasoning and chain of thought to reason about complex inputs and patterns. The larger models, in terms of parameters, excel at reasoning tasks and also in generating detailed chain of thought traces but their smaller variants often struggle to reason …
Joaquin Vanschoren
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Shawon Ashraf
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Advanced Models with AMOR/e
If you are a bright student, want to work on advanced AI models (e.g. multimodal foundation models), and you have a clear vision on what you want to research, check whether it matches the research done in the AMOR/e research group. Our mission is …
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Joaquin Vanschoren
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[NXP] Emergent learning paradigms
This project is about exploring emergent learning paradigms, such as Continual learning and On-device learning. The exact topic will be further defined based on interviews with the company.Note: this is an industry topic and will require interviews with the company
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Joaquin Vanschoren
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[NXP] Efficient Architectures
The current generation of dense transformer methods is too expensive for many practical applications. In this project you will explore novel families of (post-transformer) architectures that are much more efficient.Possible directions include:* State-space models* Hybrid Architectures (eg. State-Space-model + Transformer architectures)* (quantization-aware) Diffusion LMs* …
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Joaquin Vanschoren
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[NXP] Efficient AI models
Current AI models are too large and expensive for practical applications. You are asked to explore one of the techniques below (or a combination) to make them more efficient: Speculative Decoding:* Vision Language Model Speculative Decoding* Grammar based Drafters with Token Tree Verification* Speculative Decoding …
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Joaquin Vanschoren
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[ATOS] GenAI Evaluation Harness
Problem DefinitionGenAI systems deliver inconsistent quality (hallucinations, poor retrieval, variable latency). Customers want predictable KPIs and a reliable evaluation framework.ObjectiveDevelop an evaluation harness that automatically tests GenAI systems on:* Groundedness & correctness* Hallucination detection* Retrieval quality (RAG)* Latency & token costs* Robustness under variations* …
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Joaquin Vanschoren
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Dialects and Low-Resource Languages in LLMs
In multilingual natural language processing (NLP) we distinguish languages based on their resourcefulness. This indicates the amount of resources available for a given language. On the Common Crawl statistics page we can clearly see that data crawled from the internet is predominantly English, followed …
Joaquin Vanschoren
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Dalton Harmsen
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Fine-Tuning Vision-Language Models for Industrial Fruit Packing
Recent vision-language-action (VLA) and vision-language models (VLMs) show strong promise for robot learning, but their practical value for industrial cells remains unclear. This thesis focuses on a more relevant question than public benchmarking alone: can a fine-tuned VLA or VLM outperform an already existing …
Bram Grooten
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Joaquin Vanschoren
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Large Models for Robotic Manipulation in Healthcare: Dual- Arm Large model performance in Real-World Deployments
ObjectiveThe goal of this project is to train, deploy and evaluate embodied multimodal (large) models to perform dual-arm manipulation tasks relevant to healthcare assistance. The student will work towards a demonstration task. In the work leading up to the demonstration, the student will train …
Bram Grooten
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Joaquin Vanschoren
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Building an AI avatar
This project is for Dutch-speaking students only, since it requires working with large amounts of Dutch data and requires Dutch cultural knowledge.This project aims to create an AI avatar that is trained to act like a well-known Dutch entertainer. It is to be trained …
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Joaquin Vanschoren
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From Tables to Pixels: Adapting Tabular Foundation Models for Vision Tasks
Foundation models have recently demonstrated remarkable capabilities across a wide range of domains by learning from large-scale data and generalizing to novel, unseen tasks without the need for fine-tuning. This generalization ability is primarily enabled by their capacity for in-context learning, which is the …
Joaquin Vanschoren
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Anna Vettoruzzo
Assigned Projects
No currently assigned Projects.
Finished Projects (43)
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Learning to Optimize at Scale with Attention MechanismsJan 2025
Continual learning refers to the ability of a system to continually acquire new knowledge over time while retaining previously learned experience [1]. Conventional neural networks typically update all model parameters (weights) when adapting to new tasks, which often leads to catastrophic forgetting [2]. Instead, …
Joaquin Vanschoren
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Anna Vettoruzzo