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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Rodríguez, J. A., Puri, A., Agarwal, S., Laradji, I., Rodríguez, P., Rajeswar, S., Vázquez, D., Pal, C. J., & Pedersoli, M. (2025, June). StarVector: Generating Scalable Vector Graphics Code from Images and Text [Paper]. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2025), Nashville, TN, USA. External link
Rodríguez, J. A., Puri, A., Agarwal, S., Laradji, I., Rajeswar, S., Vázquez, D., Pal, C. J., & Pedersoli, M. (2025, February). StarVector: Generating Scalable Vector Graphics Code from Images and Text [Paper]. 39th AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA. Published in Proceedings of the AAAI Conference on Artificial Intelligence, 39(28). External link
Masry, A., Rodriguez, J., Zhang, T., Wang, S., Wang, C., Feizi, A., Kalkunte Suresh, A., Puri, A., Jian, X., Noël, P.-A., Tejaswi Madhusudhan, S., Pedersoli, M., Liu, B., Chapados, N., Bengio, Y., Hoque, E., Pal, C. J., Laradji, I., Vázquez, D., ... Rajeswar Mudumba, S. (2025, December). AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding [Paper]. 39th Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, CA, USA. Published in Advances in Neural Information Processing Systems, 38. External link
Rodriguez, J., Zhang, H., Puri, A., Pramanik, R., Feizi, A., Wichmann, P., Mondal, A., Reza Samsami, M., Awal, R., Taslakian, P., Gella, S., Rajeswar, S., Vázquez, D., Pal, C. J., & Pedersoli, M. (2025, December). Rendering-Aware Reinforcement Learning for Vector Graphics Generation [Paper]. 39th Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, CA, USA. External link
Monteiro, J., Marcotte, É., Noël, P.-A., Zantedeschi, V., Vázquez, D., Chapados, N., Pal, C. J., & Taslakian, P. (2024, November). XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference [Paper]. Findings of the Association for Computational Linguistics (ACL 2024), Miami, FL, USA. External link
Vázquez, D., Bernal, J., Sánchez, F. J., Fernández-Esparrach, G., López, A. M., Romero, A., Drożdżal, M., & Courville, A. (2017). A benchmark for endoluminal scene segmentation of colonoscopy images. Journal of Healthcare Engineering, 2017, 1-9. Available
