Aarash Feizi
Visiting Researcher
AI Frontier Research
Aarash Feizi is a PhD candidate majoring in Computer Science at Mila/McGill under the supervision of Prof. Reihaneh Rabbany and Prof. Adriana Romero-Soriano. His research interests lie in image, language, and graph representation learning and self-supervision. He is currently exploring how multimodal models can help build more generalizable and robust models that can be applied to real-world datasets and applications.
Interests
- Multimodal Models
- Self supervised learning
Publications
AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding.
Neural Information Processing Systems (NeurIPS),
2025.
Rendering-Aware Reinforcement Learning for Vector Graphics Generation.
Neural Information Processing Systems (NeurIPS),
2025.
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation.
Conference on Empirical Methods in Natural Language Processing (EMNLP),
2025.
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation.
Workshop at the Computer Vision and Pattern Recognition Conference (CVPR),
2025.
AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding.
Workshop at the International Conference of Learning Representation (ICLR),
2025.
WebMMU: A Benchmark for Multimodal Multilingual Website Understanding and Code Generation.
Workshop at the International Conference of Learning Representation (ICLR),
2025.
BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks.
International Conference of Learning Representations (ICLR),
2025.
BigDocs: A Permissively-Licensed Dataset for Training Vision-Language Models on Document and Code Tasks.
Workshop at the Neural Information Processing Systems (NeurIPS),
2024.