Multi-modal News Understanding with Professionally Labelled Videos (ReutersViLNews)

no code implementations • 23 Jan 2024 • Shih-Han Chou, Matthew Kowal, Yasmin Niknam, Diana Moyano, Shayaan Mehdi, Richard Pito, Cheng Zhang, Ian Knopke, Sedef Akinli Kocak, Leonid Sigal, Yalda Mohsenzadeh

Towards a solution for designing this ability in algorithms, we present a large-scale analysis on an in-house dataset collected by the Reuters News Agency, called Reuters Video-Language News (ReutersViLNews) dataset which focuses on high-level video-language understanding with an emphasis on long-form news.

Miscellaneous Video Description

Domain Specific Fine-tuning of Denoising Sequence-to-Sequence Models for Natural Language Summarization

no code implementations • 6 Apr 2022 • Brydon Parker, Alik Sokolov, Mahtab Ahmed, Matt Kalebic, Sedef Akinli Kocak, Ofer Shai

Summarization of long-form text data is a problem especially pertinent in knowledge economy jobs such as medicine and finance, that require continuously remaining informed on a sophisticated and evolving body of knowledge.

Data Augmentation Denoising

An Experimental Evaluation of Transformer-based Language Models in the Biomedical Domain

no code implementations • 31 Dec 2020 • Paul Grouchy, Shobhit Jain, Michael Liu, Kuhan Wang, Max Tian, Nidhi Arora, Hillary Ngai, Faiza Khan Khattak, Elham Dolatabadi, Sedef Akinli Kocak

With the growing amount of text in health data, there have been rapid advances in large pre-trained models that can be applied to a wide variety of biomedical tasks with minimal task-specific modifications.

NER