From the 1 of 8 linked papers with an AI index.
8 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…
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…
Perturbation Self-Supervised Representations for Cross-Lingual Emotion TTS: Stage-Wise Modeling of Emotion and Speaker
Cheng Gong, Chunyu Qiang, Tianrui Wang +7
Cross-lingual emotional text-to-speech (TTS) aims to produce speech in one language that captures the emotion of a speaker from another language while maintaining the target voice'…
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…