MUCG Workshop at ECCV 26 · 2026

Combining Finetuning and RAG for Structured Output Prediction on a Multimodal High Velocity Retail Dataset

Bianca Lamm, Janis Keuper

Why this publication matters

Retail information changes quickly, so a prediction system must handle both new products and changing details. This work studies combining model fine-tuning with retrieval of relevant examples for extracting structured information. The practical motivation is to make specialized knowledge and up-to-date context work together in one pipeline.

Abstract

The original abstract will be added when the full paper is available.

Figures

Additional figures and captions will be added when the full paper is available.

Cite this paper

Download .bib

@inproceedings{lamm2026combiningfinetuningand96,
  title = {{Combining Finetuning and RAG for Structured Output Prediction on a Multimodal High Velocity Retail Dataset}},
  author = {Bianca Lamm and Janis Keuper},
  booktitle = {MUCG Workshop at ECCV 26},
  year = {2026},
  url = {https://openreview.net/pdf?id=H4fdIUP8Jd}
}

Figures and abstract are reproduced from the linked research sources. Credit remains with the authors and publishers.