Author: Saba Zolfaghari
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Comparative analysis of fashion captioning and multimodal fashion recommendation
Author: Maria De Los Angeles Gwendolyn Aglae Rippberger Fonseca Supervisor: Julia Neidhardt Abstract This thesis explores two main tasks: (1) fine-tuning image captioning models for fashion datasets and (2) evaluating different feature spaces for personalized fashion recommendations. We fine-tune state-of-the-art vision-language models – BLIP-2 and LLaVA – on two fashion datasets, H&M and FACAD, to…
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The impact of using Large Language Models on the performance of Recommender Systems
Author: Michael Schmiedmayer Supervisor: Julia Neidhardt, Co-Supervisor: Ahmadou Wagne Abstract This thesis investigates the integration of Large Language Models (LLMs) into Conversational Recommender Systems (CRSs), evaluating the impact of model scale and hyperparameter configurations on retrieval performance. Moving beyond purely synthetic benchmarks, this research introduces a novel, end-to-end evaluation framework grounded in real-world user behaviour.…
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Evaluating Agentic Retrieval Augmented Generation in Open Tender Evaluations
Author: Franz Ottitsch Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Public tender evaluation requires contracting authorities to assess bidder responses against defined award criteria across long, semi structured documents, a process that remains largely manual, time consuming and costly. Retrieval augmented generation (RAG) systems, particularly agentic variants with iterative retrieval and task decomposition, offer…