Official reports and documents detailing our project`s progress, methodologies and results.

• M. Tzelepi, N. Dimitriou, C. Gkogkos, and D. Tzovaras, “Improving zero-shot industrial defect detection exploiting LMMs as inverse reasoners,” in 2026 IEEE International Conference on Image Processing, 13–17 September 2026. [Online]. Available: https://zenodo.org/records/20178340
• M. Tzelepi, N. Dimitriou, C. Gkogkos, and D. Tzovaras, “LMM-assisted Subclass-Aware Zero-Shot Industrial Defect Detection,” in 34th European Signal Processing Conference 2026 (EUSIPCO), 31 August – 4 September 2026. [Online]. Available: https://zenodo.org/records/20179154
• Z. Ju, Q. Wang, D. O’Reilly-Morgan, E. Tragos, N. Hurley, R. Dong, and A. Lawlor, “Transfer Learning via User-Item Graph Convolution for Enhanced Cross-Domain Recommendation,” in Proc. 19th ACM International Conference on Web Search and Data Mining (WSDM), 21 February 2026. [Online]. Available: https://dl.acm.org/doi/10.1145/3773966.3779398
• A. Tzelepakis, N. Dimitriou, P. Charalampous, K. Tsongas, D. Tzetzis, and D. Tzovaras, “Generative Models Training Based on FEM Simulations Toward Improved Defect Detection,” IEEE Transactions on Instrumentation and Measurement, 13 May 2025. [Online]. Available: https://ieeexplore.ieee.org/document/11002741

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