---
res:
  bibo_abstract:
  - In recent years, Retrieval Augmented Generation (RAG) has emerged as a promising
    technology for designing application-specific chatbots. RAG combines a Large Language
    Model (LLM) with application-specific information provided via a database. This
    opens up the possibility for companies to at least partially automate existing
    business processes using RAG. One use case relates to work preparation at a mechanical
    engineering company. Due to the high complexity of the products and the wide variety
    of variants, creating assembly instructions for individual assemblies and modules
    involves a considerable amount of administrative work. The use of RAG can help
    to significantly improve the efficiency of this process. However, a key challenge
    is to ensure high quality of automatically generated assembly instructions. While
    existing research has focused on feedback mechanisms for improving LLMs, the effectiveness
    of different prompt-based feedback types on RAG-generated technical documentation
    quality has not yet been sufficiently investigated. This article therefore explores
    how quality of assembly instructions can be improved by integrating feedback mechanisms
    into a RAG system. For this purpose, two different feedback mechanisms were used
    in a laboratory experiment. On the one hand, an exclusively quantitative feedback
    mechanism was used. On the other hand, quantitative and qualitative feedback were
    combined. The results demonstrate that feedback mechanisms contribute to improving
    quality of information in assembly instructions. In addition, it was found that
    exclusively quantitative feedback leads to similarly good results as more complex
    combined feedback.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Julia
      foaf_name: Becker, Julia
      foaf_surname: Becker
  - foaf_Person:
      foaf_givenName: Benjamin
      foaf_name: Adrian, Benjamin
      foaf_surname: Adrian
      foaf_workInfoHomepage: http://www.librecat.org/personId=42266
  - foaf_Person:
      foaf_givenName: Dominik
      foaf_name: Green, Dominik
      foaf_surname: Green
      foaf_workInfoHomepage: http://www.librecat.org/personId=85489
  - foaf_Person:
      foaf_givenName: Sven
      foaf_name: Hinrichsen, Sven
      foaf_surname: Hinrichsen
      foaf_workInfoHomepage: http://www.librecat.org/personId=49010
  bibo_doi: 10.1016/j.procir.2026.03.242
  bibo_volume: 146
  dct_date: 2026^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2212-8271
  dct_language: eng
  dct_publisher: Elsevier BV@
  dct_title: Evaluating feedback mechanisms in the automatic creation of assembly
    instructions using retrieval-augmented generation@
...