1 code implementation • 30 Nov 2022 • Yookoon Park, Mahmoud Azab, Bo Xiong, Seungwhan Moon, Florian Metze, Gourab Kundu, Kirmani Ahmed
Cross-modal contrastive learning has led the recent advances in multimodal retrieval with its simplicity and effectiveness.
no code implementations • 10 Oct 2022 • Pedro Rodriguez, Mahmoud Azab, Becka Silvert, Renato Sanchez, Linzy Labson, Hardik Shah, Seungwhan Moon
Searching troves of videos with textual descriptions is a core multimodal retrieval task.
1 code implementation • LREC 2020 • Santiago Castro, Mahmoud Azab, Jonathan Stroud, Cristina Noujaim, Ruoyao Wang, Jia Deng, Rada Mihalcea
We introduce LifeQA, a benchmark dataset for video question answering that focuses on day-to-day real-life situations.
no code implementations • CONLL 2019 • Mahmoud Azab, Noriyuki Kojima, Jia Deng, Rada Mihalcea
We introduce a new embedding model to represent movie characters and their interactions in a dialogue by encoding in the same representation the language used by these characters as well as information about the other participants in the dialogue.
no code implementations • IJCNLP 2019 • Mahmoud Azab, Stephane Dadian, Vivi Nastase, Larry An, Rada Mihalcea
We introduce a new dataset consisting of natural language interactions annotated with medical family histories, obtained during interactions with a genetic counselor and through crowdsourcing, following a questionnaire created by experts in the domain.
no code implementations • 19 Nov 2018 • Konstantinos Pappas, Mahmoud Azab, Rada Mihalcea
The geolocation of online information is an essential component in any geospatial application.
no code implementations • NAACL 2018 • Mahmoud Azab, Mingzhe Wang, Max Smith, Noriyuki Kojima, Jia Deng, Rada Mihalcea
We propose a new model for speaker naming in movies that leverages visual, textual, and acoustic modalities in an unified optimization framework.