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I am a research engineer at Meta Research (FAIR) focusing on machine translation and multimodal understanding. Previously I worked on computer vision for AR/VR at Meta Reality Labs. I did my Masters in machine learning from Georgia Tech. Before that, I received a Bachelor's degree in computer science from NITS, India and worked briefly at Samsung Camera R&D. Email / Github / Google Scholar / LinkedIn / Twitter |
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My research focuses on machine learning, computer vision and natural language processing. In particular, I am interested in large scale self supervised training, multitask learning for multimodal understanding and machine translation. |
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NLLB Team*, Marta R. Costa-jussa*, James Cross*, Onur Celebi*, Maha Elbayad*, Kenneth Heafield*, Kevin Heffernan*, Elahe Kalbassi*, Janice Lam*, Daniel Licht*, Jean Maillard*, Anna Sun*, Skyler Wang*, Guillaume Wenzek*, Al Youngblood*, Bapi Akula, Loic Barrault, Gabriel Mejia Gonzalez, Prangthip Hansanti, John Hoffman, Semarley Jarrett, Kaushik Ram Sadagopan, Dirk Rowe, Shannon Spruit, Chau Tran, Pierre Andrews†, Necip Fazil Ayan†, Shruti Bhosale†, Sergey Edunov†, Angela Fan†, Cynthia Gao†, Vedanuj Goswami†, Francisco Guzman†, Philipp Koehn†, Alexandre Mourachko†, Christophe Ropers†, Safiyyah Saleem†, Holger Schwenk†, Jeff Wang† † Research and engineering leadership, equal contribution arxiv / website / code / demo A massively multilingual model that can translate between any pair among 200+ languages. |
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Amanpreet Singh*, Ronghang Hu*, Vedanuj Goswami*, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, Douwe Kiela * equal contribution CVPR, 2022 arxiv / website / code A foundaltional model for vision and language alignment, that can perform vision, language, and cross- and multi-modal vision and language tasks. |
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Songwei Ge, Vedanuj Goswami, Larry Zitnick, Devi Parikh ICLR, 2021 arxiv / bibtex / slides Two new datasets for creative skecthes and a novel model(DoodlerGAN) to generate unseen compositions of novel part appearances. |
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Duy-Kien Nguyen, Vedanuj Goswami, Xinlei Chen ICLR, 2021 arxiv / bibtex / slides Modulated convolutional bottleneck architecture for improving visual counting, which achieves SOTA in VQA and winner of 2020 VQA Challenge at CVPR. |
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Sasha Sheng, Amanpreet Singh, Vedanuj Goswami, Jose Magana, Tristan Thrush, Wojciech Galuba, Devi Parikh, Douwe Kiela NeurIPS, 2021 arxiv / website / bibtex / slides Adversarial dataset and benchmark that is collected with Human-and-Model-in-the-loop for evaluating the robustness of state-of-the-art VQA systems. |
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Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, Davide Testuggine NeurIPS, 2020 arxiv / blog / bibtex / code New benchmark for multimodal classification, focusing on detecting hate speech in multimodal memes. |
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Laura Sevilla-Lara, Shengxin Zha, Zhicheng Yan, Vedanuj Goswami, Matt Feiszli, Lorenzo Torresani WACV, 2021 arxiv / blog / bibtex A methodology to discover the relevance of temporal information in action classes and use it to identify categories that contain more temporal information (temporal classes). |
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Jiasen Lu*, Vedanuj Goswami*, Marcus Rohrbach, Devi Parikh, Stefan Lee * equal contribution CVPR, 2020 arxiv / bibtex An approach for effective multi-task learning. Trained a single model on 12 popular vision-and-language tasks improving upon individual task-specific models. datasets.. |
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Albert Pumarola, Vedanuj Goswami, Francisco Vicente, Fernando De la Torre, Francesc Moreno-Noguer ICCV Workshop, 2019 website Unsupervised photo-realistic transfer of clothing of a person in a reference image into another person in an unconstrained image or video. |
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Spencer Rugaber, Shruti Bhati, Vedanuj Goswami, Evangelia Spiliopoulou, Sasha Azad, Sridevi Koushik, Rishikesh Kulkarni, Mithun Kumble, Sriya Sarathy, Ashok Goel ICCBR, 2016 pdf / blog / poster / bibtex NLP framework for extracting partial SBF (Structure, Behavior, Function) models of biological systems from natural language documents for potential use in biologically inspired design. |
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Vedanuj Goswami, Samir Borgohain ACALCI, 2015 code / bibtex Algorithm to differentiate between correct and wrong grammatical sentence constructs using artificial immune networks. |
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