

Factify5WQA - Please visit this link for details.
Combating fake news is one of the burning societal crisis. It is difficult to expose false claims before they create a lot of damage. Automatic fact/claim verification has recently become a topic of interest among diverse research communities. Research efforts and datasets on text fact verification could be found, but there is not much attention towards multimodal or cross-modal fact-verification. This workshop will encourage researchers from interdisciplinary domains working on multimodality and/or fact checking to come together and work on multimodal (images, memes, videos) fact checking. At the same time, multimodal hate speech detection is an important problem but has not received much attention. Lastly, learning joint modalities his of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums.
During the last decade, both the field of studies - NLP and CV have made significant progress due to the success strories of neural network. Mutimodal tasks like visual question-answering (VQA), image captioning, video captioning, caption based image retrieval, etc. started getting into the main spotlight either in NLP/CV forums. Mutimodality is the next big leap for the AI community. De-Factify is a specified forum to discuss on multimodal fake news, and hate speech related challenges. We also encourage discussion on multimodal tasks in general.
Link to previous year's workshop : Defactify @ AAAI 2023
Social media for news consumption is double edged sword. On the one hand, its low cost, easy access and rapid circulation of information lead people to consume news from social media. On the other hand, it enables the wide spread of fake news, i.e., low quality news with the false information. It affects everyone including government, media, individual, health, law and order, and economy. Therefore, fake news detection on social media has recently become an appealing research topic. We encourage solution to fake news like automated fact checking at scale, early detction of fake news etc.
We present a pioneering endeavor: a challenge focused on the automatic blurring of offensive segments within a hateful image. In the context of multimodal content (comprising both text and image) infused with hate, the objective is to pinpoint the pertinent hateful portions within the image and effectively apply blurring techniques to obfuscate the malevolent aspects and thus, mitigate the antagonism conveyed by the media.
It is a forum to bring attention towards collecting, measuring, managing, mining, and understanding multimodal disinformation, misinformation, and malinformation data from social media. This workshop covers (but not limited to) the following topics: --
Paper Submission Link : EasyChair
Bias Detection in Text with Dual Transformer Classifier. Shaina Raza, Shardul Ghuge, Fatemeh Tavakoli, Sana Ayromlou and Syed Raza Bashir
Ontology Enhanced Claim Detection. Z. Melce Hüsünbeyi and Tatjana Scheffler
Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. Minh-Hao Van and Xintao Wu
Team Trifecta at Factify5WQA: Setting the Standard in Fact Verification with Fine-Tuning. Shang-Hsuan Chiang, Ming-Chih Lo, Lin-Wei Chao and Wen-Chih Peng
SRLFactQA at Factify5WQA: Composite Claim-Evidence Consistency Aware Semantic Role Labelling based Question-Answering Entailment. Hariram Veeramani, Surendrabikram Thapa, Rajaraman Kanagasabai and Usman Naseem
UniteToModerate at DeHate: The Winning Approach for Segmentation-based Content Moderation with Vision-Text-Mask Modality Fused Large Multimodal Models. Hariram Veeramani, Surendrabikram Thapa, Rajaraman Kanagasabai and Usman Naseem
Dr. Amitava Das is a Core Faculty & Research Associate Professor of the
Artificial Intelligence Institute, at the University of South Carolina, and an
Advisory Scientist to Wipro AI.
Research interests : Code-Mixing
and Social Computing.
Organizing Activities [selective] :
• Memotion @SemEval2020 • SentiMix @SemEval2020 • Computational Approaches to
Linguistic Code-Switching @LREC 2020 • CONSTRAINT @AAAI2021
Dr. Amit Sheth is the founding Director of the Artificial Intelligence
Institute, and a CSE Professor at
University of South Carolina.
Research interests : Knowledge
Graph, NLP, Analysing Social
Media
Organizing Activities [selective] :
• Cysoc2021 @ ICWSM2021 • Emoji2021 @ICWSM2021 • KiLKGC 2021 @KGC21
Dr. Asif Ekbal is an Associate Professor of CSE at IIT Patna, India.
Research interests : NLP, CodeMixing and Social Computing.
Organizing Activities [selective] : • CONSTRAINT @AAAI2021
Aman Chadha is an Applied Sci-
ence Manager at Amazon Alexa AI
and a Researcher at Stanford AI.
Research interests : Multimodal AI, On-device AI, and
Human-Centered AI.