News – CDL-RecSys

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…

Examining Tech Bias – Analyzing Career Recommendations in LLMs through Demographic Persona-Based Prompting

Supervisor: Julia Neidhardt

Survey Paper Just Accepted at ACM TORS

We are pleased to share that our survey paper, “Conversational Recommender Systems Using Generative Models (Gen-CRS): A Literature Review,” has been accepted for publication in ACM Transactions on Recommender Systems (TORS). The paper provides a comprehensive review of research on Generative Conversational Recommender Systems (Gen-CRS). As large language models and other generative technologies increasingly influence…