From the 1 of 6 linked papers with an AI index.
6 papers
ARMOR++: Agentic Orchestration of a Multi-Domain Primitive Set for Transferable Attacks on Deepfake Detectors
Christos Korgialas, Gabriel Lee Jun Rong, Dion Jia Xu Ho +3
ARMOR++ is a multi‑agent system that uses vision‑language and large language models to coordinate several attack primitives, creating highly transferable adversarial examples that…
I Know What You Meme, Even If it Emerged Today: Understanding Evolving Memes through Open-World Knowledge Acquisition
Shanhong Liu, Rui Cao, Pai Chet Ng +1
Multimodal memes are dynamic and often require up to date background knowledge for interpretation. Existing methods often overlook such knowledge or rely on fixed parametric knowle…
CLARITY: Contextual Linguistic Adaptation and Accent Retrieval for Dual-Bias Mitigation in Text-to-Speech Generation
Crystal Min Hui Poon, Pai Chet Ng, Xiaoxiao Miao +4
Instruction-guided text-to-speech (TTS) research has reached a maturity level where excellent speech generation quality is possible on demand, yet two coupled biases persist in red…
ARMOR: Agentic Reasoning for Methods Orchestration and Reparameterization for Robust Adversarial Attacks
Gabriel Lee Jun Rong, Christos Korgialas, Dion Jia Xu Ho +3
Existing automated attack suites operate as static ensembles with fixed sequences, lacking strategic adaptation and semantic awareness. This paper introduces the Agentic Reasoning…
MS-GAGA: Metric-Selective Guided Adversarial Generation Attack
Dion J. X. Ho, Gabriel Lee Jun Rong, Niharika Shrivastava +3
We present MS-GAGA (Metric-Selective Guided Adversarial Generation Attack), a two-stage framework for crafting transferable and visually imperceptible adversarial examples against…
Exploring Machine Learning and Language Models for Multimodal Depression Detection
Javier Si Zhao Hong, Timothy Zoe Delaya, Sherwyn Chan Yin Kit +2
This paper presents our approach to the first Multimodal Personality-Aware Depression Detection Challenge, focusing on multimodal depression detection using machine learning and de…