Ducho 20: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation
<|reference_start|>Ducho 20: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation: In this work, we introduce Ducho 2.0, the latest stable version of our framework. Differently from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and import of custom extraction models fine-tuned on specific tasks and datasets. Moreover, the new version is capable of extracting and processing features through multimodal-by-design large models. Notably, all these new features are supported by optimized data loading and storing to the local memory. To showcase the capabilities of Ducho 2.0, we demonstrate a complete multimodal recommendation pipeline, from the extraction/processing to the final recommendation. The idea is to provide practitioners and experienced scholars with a ready-to-use tool that, put on top of any multimodal recommendation framework, may permit them to run extensive benchmarking analyses. All materials are accessible at: \url{https://github.com/sisinflab/Ducho}.<|reference_end|>
@article{attimonelli2024ducho,
    title={Ducho 2.0: Towards a More Up-to-Date Unified Framework for the
  Extraction of Multimodal Features in Recommendation},
    author={Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo,
  Giuseppe Gassi, Tommaso Di Noia},
    journal={arXiv preprint arXiv:2403.04503},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.04503},
    primaryClass={cs.IR}
}