6 papers
PRISM: Powerful Time Series to Image (TS2I) Representations for Multivariate Anomaly Detection
Mateusz Smendowski, Kamil Faber, Piotr Nawrocki +2
Time series anomaly detection (TSAD) underpins applications in predictive maintenance, finance, and cloud computing, however performance remains sensitive to representation choices…
Decoding Islamophobic Discourse: Using LLMs to Identify Tropes and Semi-Coded Hate Speech
Raza Ul Mustafa, Roi Dupart, Gabrielle Smith +2
In recent years, Islamophobia has gained significant traction across Western societies, fueled by the rise of digital communication networks. This paper performs a large-scale anal…
MOMENTA: Mixture-of-Experts Over Multimodal Embeddings with Neural Temporal Aggregation for Misinformation Detection
Yeganeh Abdollahinejad, Ahmad Mousavi, Naeemul Hassan +4
The widespread dissemination of multimodal content on social media has made misinformation detection increasingly challenging, as misleading narratives often arise not only from te…
SoftHateBench: Evaluating Moderation Models Against Reasoning-Driven, Policy-Compliant Hostility
Xuanyu Su, Diana Inkpen, Nathalie Japkowicz
Online hate on social media ranges from overt slurs and threats (\emph{hard hate speech}) to \emph{soft hate speech}: discourse that appears reasonable on the surface but uses fram…
E-CaTCH: Event-Centric Cross-Modal Attention with Temporal Consistency and Class-Imbalance Handling for Misinformation Detection
Ahmad Mousavi, Yeganeh Abdollahinejad, Roberto Corizzo +2
Detecting multimodal misinformation on social media remains challenging due to inconsistencies between modalities, changes in temporal patterns, and substantial class imbalance. Ma…
HateSieve: A Contrastive Learning Framework for Detecting and Segmenting Hateful Content in Multimodal Memes
Xuanyu Su, Yansong Li, Diana Inkpen +1
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…