A Deep Learning Approach to Persian Plagiarism Detection. - Erfaneh Gharavi; Kayvan Bijari; Kiarash Zahirnia; Hadi Veisi (FIRE (Working Notes), 2016)

A Fast Multi-level Plagiarism Detection Method Based on Document Embedding Representation. - Erfaneh Gharavi; Hadi Veisi; Kayvan Bijari; Kiarash Zahirnia (FIRE Workshop, 2016)

Generating the Graph Gestalt: Kernel-Regularized Graph Representation Learning. - Kiarash Zahirnia; Ankita Sakhuja; Oliver Schulte; Parmis Nadaf; Ke Li 011; Xia Hu (CoRR, 2021)

Deep Learning of Latent Edge Types from Relational Data. - Kiarash Zahirnia; Oliver Schulte; Ke Li 011; Ankita Sakhuja; Parmis Naddaf (Canadian AI, 2022)

Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. - Kiarash Zahirnia; Oliver Schulte; Parmis Naddaf; Ke Li 011 (NeurIPS, 2022)

Joint Link Prediction Via Inference from a Model. - Parmis Naddaf; Erfaneh Mahmoudzaheh Ahmadi Nejad; Kiarash Zahirnia; Manfred Jaeger; Oliver Schulte (CIKM, 2023)

Neural Graph Generation from Graph Statistics. - Kiarash Zahirnia; Yaochen Hu 001; Mark Coates; Oliver Schulte (NeurIPS, 2023)

Deep Generative Models for Subgraph Prediction. - Erfaneh Mahmoudzadeh; Parmis Naddaf; Kiarash Zahirnia; Oliver Schulte (ECAI, 2024)

A Fourier Space Perspective on Diffusion Models. - Fabian Falck; Teodora Pandeva; Kiarash Zahirnia; Rachel Lawrence; Richard E. Turner; Edward Meeds; Javier Zazo; Sushrut Karmalkar (CoRR, 2025)

ETT: Expanding the Long Context Understanding Capability of LLMs at Test-Time. - Kiarash Zahirnia; Zahra Golpayegani; Walid Ahmed; Yang Liu (CoRR, 2025)