no code implementations • 11 Aug 2024 • Xuanyu Su, Yansong Li, Diana Inkpen, Nathalie Japkowicz
Amidst the rise of Large Multimodal Models (LMMs) and their widespread application in generating and interpreting complex content, the risk of propagating biased and harmful memes remains significant.
no code implementations • 19 Jan 2024 • Dhanush Kikkisetti, Raza Ul Mustafa, Wendy Melillo, Roberto Corizzo, Zois Boukouvalas, Jeff Gill, Nathalie Japkowicz
The posts are scraped using seed expressions related to previously known discourse of hatred towards Jews.
no code implementations • 28 Sep 2023 • Shoffan Saifullah, Rafal Drezewski, Anton Yudhana, Andri Pranolo, Wilis Kaswijanti, Andiko Putro Suryotomo, Seno Aji Putra, Alin Khaliduzzaman, Anton Satria Prabuwono, Nathalie Japkowicz
In testing set, it achieved an accuracy of 0. 98, a sensitivity of 1 for detecting fertile eggs, and a specificity of 0. 96 for identifying non-fertile eggs.
no code implementations • 13 Aug 2023 • Evan Crothers, Herna Viktor, Nathalie Japkowicz
A common approach to quantifying neural text classifier interpretability is to calculate faithfulness metrics based on iteratively masking salient input tokens and measuring changes in the model prediction.
no code implementations • 22 Apr 2023 • Yueyang Liu, Zois Boukouvalas, Nathalie Japkowicz
The spread of misinformation in social media outlets has become a prevalent societal problem and is the cause of many kinds of social unrest.
1 code implementation • 16 Mar 2023 • Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo
Continual learning (CL) is one of the most promising trends in recent machine learning research.
1 code implementation • 14 Mar 2023 • Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz
Anomaly detection is of paramount importance in many real-world domains, characterized by evolving behavior.
1 code implementation • 13 Jan 2023 • Evan Crothers, Herna Viktor, Nathalie Japkowicz
We apply a large multilingual language model (BLOOM-176B) in open-ended generation of Chinese song lyrics, and evaluate the resulting lyrics for coherence and creativity using human reviewers.
no code implementations • 8 Dec 2022 • Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Smith, Sahana Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael Piacentino, Jesse Hostetler, Aswin Raghavan
In this paper, we introduce the Lifelong Reinforcement Learning Components Framework (L2RLCF), which standardizes L2RL systems and assimilates different continual learning components (each addressing different aspects of the lifelong learning problem) into a unified system.
no code implementations • 13 Oct 2022 • Evan Crothers, Nathalie Japkowicz, Herna Viktor
Detection of machine generated text is a key countermeasure for reducing abuse of NLG models, with significant technical challenges and numerous open problems.
1 code implementation • 2 Mar 2022 • Evan Crothers, Nathalie Japkowicz, Herna Viktor, Paula Branco
The detection of computer-generated text is an area of rapidly increasing significance as nascent generative models allow for efficient creation of compelling human-like text, which may be abused for the purposes of spam, disinformation, phishing, or online influence campaigns.
no code implementations • 18 Jan 2022 • Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz
Detecting relevant changes in dynamic time series data in a timely manner is crucially important for many data analysis tasks in real-world settings.
1 code implementation • 29 Jul 2021 • Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
Structural concept complexity, class overlap, and data scarcity are some of the most important factors influencing the performance of classifiers under class imbalance conditions.
no code implementations • 3 Dec 2020 • Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Class imbalance is a problem of significant importance in applied deep learning where trained models are exploited for decision support and automated decisions in critical areas such as health and medicine, transportation, and finance.
no code implementations • 1 Jun 2020 • Zois Boukouvalas, Christine Mallinson, Evan Crothers, Nathalie Japkowicz, Aritran Piplai, Sudip Mittal, Anupam Joshi, Tülay Adalı
Social media has become an important communication channel during high impact events, such as the COVID-19 pandemic.
1 code implementation • 29 Aug 2019 • Evan Crothers, Nathalie Japkowicz, Herna Viktor
The detection of clandestine efforts to influence users in online communities is a challenging problem with significant active development.
no code implementations • 9 Jul 2019 • Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama
We conclude that the paradigm of contexts in data streams can be used to improve the performance of streaming one-class classifiers.