3 citations · 8 across the 29 of their papers we have counts for
12 papers · 1 filter
NutriScreener: Retrieval-Augmented Multi-Pose Graph Attention Network for Malnourishment Screening
Misaal Khan, Mayank Vatsa, Kuldeep Singh +1
Child malnutrition remains a global crisis, yet existing screening methods are laborious and poorly scalable, hindering early intervention. In this work, we present NutriScreener,…
Right Looks, Wrong Reasons: Compositional Fidelity in Text-to-Image Generation
Mayank Vatsa, Aparna Bharati, Richa Singh
The architectural blueprint of today's leading text-to-image models contains a fundamental flaw: an inability to handle logical composition. This survey investigates this breakdown…
TAIGen: Training-Free Adversarial Image Generation via Diffusion Models
Susim Roy, Anubhooti Jain, Mayank Vatsa +1
Adversarial attacks from generative models often produce low-quality images and require substantial computational resources. Diffusion models, though capable of high-quality genera…
Quantum-Inspired Audio Unlearning: Towards Privacy-Preserving Voice Biometrics
Shreyansh Pathak, Sonu Shreshtha, Richa Singh +1
The widespread adoption of voice-enabled authentication and audio biometric systems have significantly increased privacy vulnerabilities associated with sensitive speech data. Comp…
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral +2
Do contemporary diffusion models preserve the class geometry of hyperspherical data? Standard diffusion models rely on isotropic Gaussian noise in the forward process, inherently f…
Multimodal Zero-Shot Framework for Deepfake Hate Speech Detection in Low-Resource Languages
Rishabh Ranjan, Likhith Ayinala, Mayank Vatsa +1
This paper introduces a novel multimodal framework for hate speech detection in deepfake audio, excelling even in zero-shot scenarios. Unlike previous approaches, our method uses c…
SynHate: Detecting Hate Speech in Synthetic Deepfake Audio
Rishabh Ranjan, Kishan Pipariya, Mayank Vatsa +1
The rise of deepfake audio and hate speech, powered by advanced text-to-speech, threatens online safety. We present SynHate, the first multilingual dataset for detecting hate speec…
LitMAS: A Lightweight and Generalized Multi-Modal Anti-Spoofing Framework for Biometric Security
Nidheesh Gorthi, Kartik Thakral, Rishabh Ranjan +2
Biometric authentication systems are increasingly being deployed in critical applications, but they remain susceptible to spoofing. Since most of the research efforts focus on moda…
Can Quantized Audio Language Models Perform Zero-Shot Spoofing Detection?
Bikash Dutta, Rishabh Ranjan, Shyam Sathvik +2
Quantization is essential for deploying large audio language models (LALMs) efficiently in resource-constrained environments. However, its impact on complex tasks, such as zero-sho…
Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models
Kartik Thakral, Tamar Glaser, Tal Hassner +2
Existing unlearning algorithms in text-to-image generative models often fail to preserve the knowledge of semantically related concepts when removing specific target concepts: a ch…
Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion
Kartik Thakral, Tamar Glaser, Tal Hassner +2
How can we effectively unlearn selected concepts from pre-trained generative foundation models without resorting to extensive retraining? This research introduces `continual unlear…
From No to Know: Taxonomy, Challenges, and Opportunities for Negation Understanding in Multimodal Foundation Models
Mayank Vatsa, Aparna Bharati, Surbhi Mittal +1
Negation, a linguistic construct conveying absence, denial, or contradiction, poses significant challenges for multilingual multimodal foundation models. These models excel in task…