Machine learningDeep learning / NLP / CV

Multimodal RoBERTa-based Classification

Multimodal RoBERTa-based Classification kombinira RoBERTa transformer enkoder — robustno optimiziranu inačicu BERT-a — s pomoćnim modali­tetima kao što su slike, strukturirani metapodaci ili tablične značajke. Spojena reprezentacija zatim se predaje klasifikacijskoj glavi, omogućujući modelu da istovremeno iskoristi bogato razumijevanje jezika i signale izvan teksta.

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Izvori

  1. Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach. arXiv preprint arXiv:1907.11692. link
  2. Kiela, D., Grave, E., Joulin, A., & Mikolov, T. (2018). Efficient Large-Scale Multi-Modal Classification. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Multimodal RoBERTa-based Classification (Text + Non-Text Fusion with RoBERTa Encoder). ScholarGate. https://scholargate.app/hr/deep-learning/multimodal-roberta-based-classification

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ScholarGateMultimodal RoBERTa-based Classification (Multimodal RoBERTa-based Classification (Text + Non-Text Fusion with RoBERTa Encoder)). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/multimodal-roberta-based-classification · Skup podataka: https://doi.org/10.5281/zenodo.20539026